Security is no longer an afterthought but an integral part of the entire software development process, much like the critical role of encryption in a banking app. Imagine a financial application handling thousands of transactions per minute; a single security flaw not caught in time can lead to massive data breaches and loss of customer trust. 

DevSecOps, blending development, security, and operations, underlines the need to weave security measures into every phase of software development, from the first line of code to the last update rolled out. Think of a scenario where you’re building a complex, cloud-based service or deploying an application on VPS hosting. Without the right set of tools used in DevSecOps, each stage — coding, deployment (including virtual machines), and maintenance — could become a potential weak spot for cyber attacks. 

In this guide, we’re going deep into the variety of DevSecOps tools. These tools work tirelessly behind the scenes, ensuring that every module, API keys, and every line of code in your software is not just functional but protected against cyber threats and other security flaws. We’ll explore the top 20 tools you should have in your arsenal in 2024, each one a key player in safeguarding your software development cycle against cybersecurity risks.

But let’s first take a look at what the DevSecOps tool is, why you need it, and how to pick the best one based on the feature set.

What are DevSecOps tools: a comprehensive overview

DevSecOps tools are essential in coding, especially when you’re dealing with complex projects. They’re not just about keeping your code safe; they’re also about making your whole development process more efficient.

Take automated security scanning tools, for example. They work in the background, checking your code for potential issues. This means you can catch bugs early, saving you a ton of time and headaches later on.

Then there’s container security. If you’re working with Docker or Kubernetes, having a tool to manage security in these environments is vital. You need DevSecOps security tools that know exactly what to look out for in these specific scenarios.

Infrastructure as Code (IaC) scanners are another key player. When you’re building your infrastructure through code, these tools make sure that everything you set up is secure and meets all necessary compliance standards.

Compliance monitoring tools are pretty handy, too. They keep an eye on your project to ensure it sticks to industry regulations, ticking all the right boxes.

Lastly, integrated DevSecOps platforms can be real time-savers due to versatile functional coverage and alerting tools. They combine various aspects of the development process, like integrating security into code and deploying it all in one place. This means less juggling between tools for you.

In short, DevSecOps tools are like the support crew in your development process, handling a lot of the technical and security details so you can focus more on the creative coding part.

Why you need DevOps security tools

Let’s talk about why having a DevOps security tool mix is non-negotiable again. Without proper security, you leave the software’s front door wide open for cyber intruders. The potential risks are no joke. Cyber threats can turn your masterpiece into a nightmare and cost you A LOT. 

Don’t believe it? 

Let’s crunch some numbers. Statistics scream the importance of DevOps security tools. Breaches are happening left, right, and center. They lead to losing data and the aftermath — damaged reputation, legal chaos, and a hit to your bottom line.

The global average cost per data breach is getting scarier and scarier every year ($4.45 million in 2023) with the highest losses attributed to the healthcare industry. However, less strictly regulated industries are still subject to data privacy regulations and need to stay compliant with the basic security requirements.

In a nutshell, it’s not a matter of if but when. DevOps security tools aren’t a luxury; they’re your lifeline. They provide the shield that keeps your software intact. So, let’s not gamble with your digital legacy. Embrace DevOps security tools, and let the statistics be a wake-up call.

Must-have features in DevSecOps tools

When you’re diving into the sea of DevSecOps tools and techniques, it’s crucial to know what floats and what sinks. Here’s a list of features to absolutely look for in the first place:

– Integration: The MVPs of DevSecOps tools play nice with your existing tech stack. Look for tools that easily integrate into your development pipeline, ensuring a smooth workflow without the headache of compatibility issues.

– Automatic web application security checks: Time is money, and in the coding universe, it’s also the key to staying ahead of the game. Top-notch DevSecOps tools automate security checks like a silent guardian. They catch vulnerabilities on the fly, saving you from late-night debugging sessions.

– Real-time threat intelligence: You need tools with radar and threat modeling. Opt for those armed with real-time threat intelligence, so you’re not just reacting to yesterday’s threats but staying one step ahead.

– User-friendly interface: Let’s keep it real — nobody has time for a tool that requires a PhD to operate. Your ideal DevSecOps security tools are user-friendly, with an interface that even your coffee-deprived coder at 3 a.m. can navigate without a hitch.

– Scalability: Your code is destined for greatness, so your tools better grow with it. Choose DevSecOps tools that scale effortlessly as your projects evolve, ensuring they’re not just for now but for the next big thing.

– Compliance: With so many regulations and standards, your tools should make compliance quick and painless. Look for those that understand and align with industry standards, saving you from regulatory headaches down the road.

Effective DevSecOps tools quietly fortify your code. Keep an eye on these features, and your toolkit will be the envy of every developer on the block.

Top 20 DevSecOps tools you can’t afford to miss

We’ve curated the ultimate lineup — the top 20 DevSecOps tools that are not a luxury but a necessity. From DevSecOps automation tools to threat management, these are the backbone of your code.

1. Check Point CloudGuard 

Ideal for enterprises navigating the cloudscape, CloudGuard is your go-to among security tools for DevSecOps that don’t compromise on speed.

Main features:

• Compatibility with leading cloud providers
• Integration into CI CD pipeline
• Intuitive dashboard for real-time insights

‘Check Point CloudGuard is ideal for intelligent prevention, agile processes, and total security controls over cloud.’ — G2 Reviewer

2. Spectral

Spectral is the watchtower for identifying and rectifying vulnerabilities. With automated policy enforcement, it ensures your code meets security standards effortlessly.

Main features:

• Code scanning
• GitHub integration
• Customizable security policies
• Developer-friendly CLI (Command Line Input)

‘Spectral changed our security. We can find issues and fix them easily. A must-have for any operations teams serious about secure coding.’ — Gartner Reviewer

3. Jit.io

Jit.io brings simplicity to secrets management and is one of the free DevSecOps tools (or Freemium). With secure storage and dynamic access control, it ensures your application secrets are locked away from prying eyes.

Main features:

• API-driven architecture
• Support for various secret types
• Easy integration with Continuous Integration and Continuous Delivery pipelines

‘Jit.io improved our secrets management. It’s easy to use, and the API-driven approach fits into our CI/CD workflow.’ — Capterra Reviewer

4. Snyk

Snyk identifies and fixes security vulnerabilities in open-source dependencies. With continuous monitoring, it ensures your dependencies stay secure over time.

Main features:

• Support for multiple languages
• Deep integration with CI/CD tools
• Actionable insights to enable developers

‘Snyk protects our entire codebase. It is one of the security tools in DevOps that not only finds vulnerabilities but guides us on how to fix them effectively.’ — G2 Reviewer

5. SonarQube

SonarQube ensures your code meets not only security standards but also maintains high-quality standards. It scans code for bugs, security vulnerabilities, and code smells.

Main features:

• Support for various languages
• Integration with popular IDEs
• Detailed code analysis reports

‘SonarQube is the code quality ensurer for our development teams. It identifies issues and provides actionable insights, making our codebase stronger.’ — Gartner Reviewer

6. OWASP ZAP

OWASP ZAP defends against web application vulnerabilities. With its comprehensive scanning capabilities, it identifies security issues and provides clear reports for remediation.

Main features:

• Active and passive scanning modes
• RESTful API for automation
• Extensive community-driven plugin architecture

‘OWASP ZAP is our go-to for web app security. It finds vulnerabilities and educates our team on best practices.’ — Capterra Reviewer

7. Checkmarx

The Checkmarx software exposure program takes a deep dive into your source code, identifying and eliminating security vulnerabilities. Its static application security testing tools (SAST) ensure that your codebase is protected against potential security threats.

Main features:

• Support for multiple languages
• Integration with popular CI/CD tools
• Centralized dashboard for comprehensive security management

‘Checkmarx elevated our security posture. Its thorough code analysis and actionable insights make it a cornerstone among our DevSecOps security tools.’ — G2 Reviewer

8. Aqua Security

Aqua Security monitors containerized environments, ensuring the security of your containers throughout their lifecycle. With its container security platform, it gives protection against container-specific threats.

Main features:

• Deep integration with major container orchestration platforms
• Runtime application self-protection
• Vulnerability scanning

‘Aqua Security leads us in securing containers. It also works well with our CI/CD pipeline. A must for containerized applications.’ — Gartner Reviewer

9. Cloud Foundry

Cloud Foundry is your ticket to cloud-native application development and deployment. With its Platform-as-a-Service (PaaS) functionality, the tool simplifies and accelerates the delivery of applications.

Main features:

• Multi-language support
• Built-in scalability
• Compatibility with major cloud providers

‘Cloud Foundry’s PaaS capabilities allow us to focus on building, not managing infrastructure.’ — G2 Reviewer

10. Sysdig

Sysdig is your observability lead in the world of containers and microservices. With real-time visibility and security, it ensures your containerized applications run smoothly and securely.

Main features:

• Container-native monitoring
• Anomaly detection
• Runtime security

‘Sysdig is our eyes and ears regarding container security. Its real-time monitoring and security features give us the confidence to run containerized applications at scale.’ — Capterra Reviewer

11. Veracode

Veracode is the duo of static and dynamic application security testing (SAST and DAST). It dives deep into your codebase, identifying vulnerabilities early in the development process and ensuring your applications are secure in production.

Main features:

• Support for multiple languages
• Integrations with popular IDEs and CI/CD tools
• Centralized platform for managing application security

‘Veracode stands out among other DevSecOps pipeline tools, catching vulnerabilities before they become headaches.’ — Gartner Reviewer

12. Qualys

Qualys is a cloud-based security solution that covers a spectrum of vulnerabilities, from web applications to network infrastructure. With its vulnerability scans management tools and continuous monitoring, Qualys provides a solid security blanket.

Main features:

• Cloud-native architecture
• Real-time threat intelligence
• Integrations with SIEM and ticketing systems

‘Qualys’s cloud-based approach and continuous monitoring give us the confidence that we’re always aware of potential issues.’ — G2 Reviewer

13. Skyhawk Security

Skyhawk Security specializes in threat detection and response, ensuring your digital realm is protected against evolving cyber threats. With its AI-driven capabilities, it provides real-time insights into potential security incidents.

Main features:

• AI-driven threat detection
• Real-time incident response
• Integration with security information and events management (SIEM) systems

‘Skyhawk Security protects well against cyber threats. Its AI-driven approach gives us real-time insights and allows us to respond swiftly to potential incidents.’ — Capterra Reviewer

14. Burp Suite

Burp Suite extensively covers web application security testing. From scanning for vulnerabilities to aiding in manual interactive application security testing, it protects all bases.

Main features:

• Dynamic scanning
• Manual security testing tools
• Community-contributed extensions

‘Burp Suite is one of the best choices for DevSecOps testing tools. It aligns with our testing approach and ensures we catch every potential vulnerability.’ — Gartner Reviewer

15. Codacy

Codacy guards your code quality, analyzing the codebase and providing insights into potential issues. With its automated tools for code reviews, it ensures your code maintains high standards.

Main features:

• Support for multiple languages,
• Integration with popular version control systems
• Intuitive dashboard for code analysis

‘Codacy automates reviews and saves us time. The actionable insights help us continuously improve the quality of our code.’ — G2 Reviewer

16. Prisma Cloud

Prisma Cloud is the sentinel for cloud-native security, providing top protection for your cloud workloads. With its multi-cloud support and container security capabilities, it ensures your cloud infrastructure remains secure and compliant.

Main features:

• Multi-cloud compatibility,
• Container security
• Integration with CI/CD pipelines

‘Prisma Cloud gives multi-cloud support and container security features, keeping us confident to accelerate our cloud-native development securely.’ — Capterra Reviewer

17. Fortify

Fortify is the leader in the static application security testing (SAST) arena. It dissects your code, identifying vulnerabilities and providing actionable insights for remediation.

Main features:

• Language support for various programming languages
• Integration with popular IDEs
• Comprehensive reporting

‘Fortify’s thorough SAST capabilities and detailed reports empower our development and security teams to build with security in mind.’ — G2 Reviewer

18. Blackduck

Blackduck is a good choice when it comes to open-source DevSecOps tools, scanning your codebase for vulnerabilities in third-party software components. With its continuous monitoring, it ensures your dependencies remain secure over time.

Main features:

• Support for multiple languages
• Integration with CI/CD pipelines
• Knowledge base of DevSecOps tools open-source components

‘Blackduck assists against open-source vulnerabilities. It provides continuous monitoring and a comprehensive database of components to help us stay ahead of potential threats.’ — Gartner Reviewer

19. Coverity

Coverity is the code quality gatekeeper, ensuring your software is free from defects and vulnerabilities. With its static code analysis tool, it identifies issues early in the development process.

Main features:

• Support for various languages
• Integration with popular IDEs
• Detailed code analysis reports

‘Coverity is our code perfection tool. We really enjoy deep static analysis tool capabilities.’ — G2 Reviewer

20. Jenkins

Jenkins is the automation pro among DevSecOps security tools, following your CI/CD pipelines with finesse. With its extensibility and vast plugin ecosystem, it automates the build, test, and deployment security processes.

Main features:

• Support for various plugins
• Integration with popular version control systems
• Flexibility in pipeline configuration

‘Jenkins is good at extensibility and ease of use to improve our CI/CD pipelines and allow us to deliver software faster and more reliably.’ — Gartner Reviewer

Conclusion: Protecting success with DevSecOps tools

The right DevSecOps tools ensure that your software meets high-quality standards and stands resilient against the relentless tide of cyber threat models. As we wrap up our exploration of the top DevSecOps tools, it’s evident that the key lies in choosing tools that align with your unique development needs and security aspirations.

These DevSecOps tools aren’t just about identifying vulnerabilities; they’re your partners in creating a robust, efficient, and secure software development lifecycle. From the cloud guardianship of Check Point CloudGuard to the secure code perfection pursuit of Codacy, each tool brings its own strengths to the table.

All of the best DevSecOps tools integrate well with CI/CD, encounter a good community, and promise scalability. Though they do differ in some aspects. Let’s break down their prowess with a quick DevSecOps tools comparison table.

DevSecOps tools list comparison

As evident, the DevOps as a Service pricing and strategy will differ among mobile app platforms, not to mention the specific stack linked with each. Ensure that your DevOps team possesses hands-on expertise in the precise mobile development approach you choose for your product.

Securing your software future with Timspark

At Timspark, we prioritize protecting applications and software supply chain with DevSecOps security tools. With a proven track record, cutting-edge solutions, and an adaptive approach, we’re your partner in the confusing and dynamic cybersecurity landscape.

Why Timspark?

– Proven success: Check out our top-tier DevOps tools, security, and other solutions for various software types.
– Modern solutions: Borrow our commitment to investing in the latest tools and strategies. Let us advise on how to select DevSecOps tools for secure software delivery.
– Adaptive approach: We tailor security tools for DevOps to your unique needs, whether in cloud-native development, traditional applications, or hybrid environments.

Integrate security into your software future with this list of DevSecOps tools and Timspark. Explore our DevSecOps services for an innovative approach where software security meets excellence. Don’t wait — fortify your software today!

Mobile app development has evolved way beyond just brainstorming innovative ideas and writing clean code. Success here hinges on the smooth collaboration between the dev and operations departments. That’s why DevOps as a Service has been gradually changing how mobile applications are built, tested, and pushed out into the world.

Let’s break it down further in the post and reveal the best impact it may have on your mobile app development project.

Why go for DevOps as a Service in mobile development?

DevOps as a Service, in simple terms, unites the brains behind development (Dev) and the guys handling operations (Ops). This blend is possible through a cloud-based service that focuses on teamwork, automation, and constantly keeping a watchful eye on the entire process. DevOps, as a managed service in mobile app development, ensures a painless and fast creation, testing, and deployment of applications across various devices and platforms.

Imagine a team making up a banking mobile app, and they go for a DevOps as a Service model. Automated testing is tailored for financial transactions, ensuring stringent security and compliance standards, while continuous integration swiftly identifies and rectifies issues related to features like fund transfers, account balances, and transaction histories. 

This helps speed up the app’s creation, testing, and release. It means they can fix issues faster, reduce mistakes, and end up with a more dependable final app.

Implementing DevOps as a Service for mobile development brings a bunch of awesome benefits:

Quicker time-to-market: DevOps as a Service makes development faster, so companies can release their apps speedily.

Better teamwork: It helps teams work together smoothly, even if they’re in different places, which means better collaboration and sharing ideas.

Higher quality: Automation and constant testing make sure the apps are of great quality and work really well.

Saving money: Going for DevOps as a managed service lowers infrastructure costs and makes better use of resources, which saves money in the long term.

Let’s explore what exactly DevOps as a Service companies do to achieve these attractive outcomes.

What Exactly DevOps as a Service companies offer to mobile development

DevOps as a Service for mobile development is all about tackling the specific challenges of building mobile apps. Here’s what DevOps as a Service providers offer in the context of mobile development.

Automated build and continuous integration (CI)

DevOps as a Service automates the building of mobile apps, making sure that code changes get integrated, validated, and tested regularly. It assumes the entire infrastructure support (dev, stage, and prod environments). This speeds up things and fosters a transparent development process, cutting down on errors and amping up the quality of the code.

Picture a mobile app team at a social media company. They’re using DevOps, and when a developer drops some new code into their code stash, the computer robots take over, testing everything automatically on different phones and systems. This way, they catch and fix problems early, and then they add new things to the app.

Cross-platform support

Mobile DevOps as a Service companies provide solutions for managing cross-platform development. This includes tools and processes for building and testing apps that smoothly run on both iOS and Android. The goal is to deliver the best and uniform user experience across diverse gadgets.

App distribution and deployment automation

DevOps services help with the automated distribution of mobile apps to various app stores or enterprise distribution platforms. This involves managing deployment pipelines, versioning, and automating releases, making it easier to roll out updates and new features.

Integrations

Trendy mobile apps always want to be the ultimate all-in-one tool. So, the mobile DevOps needs to ensure everything connects as needed and without unnecessary developer attention to side things like API keys, passwords, etc.

DevOps helps connect the apps with other services like social media, weather forecasts, maps, ChatGPT, and even favorite music apps. All this without interrupting the development cycle.

Testing and quality assurance

DevOps practices for mobile development put a spotlight on automated testing for different devices, screen sizes, and operating system versions. This guarantees that the app performs reliably and consistently across a diverse array of mobile devices.

Imagine a team developing a popular iOS app that is used by millions of users. In a traditional development process without automated testing, they make a significant change to the app’s core functionality, but they don’t catch a critical bug during manual testing. This bug goes unnoticed until the app is released to users, resulting in a massive failure.

Monitoring

DevOps ensures monitoring throughout the development process, such as adding monitoring of builds. Monitoring usually includes:

• Monitoring builds before TestFlight
  
  Before deploying a beta version to TestFlight, monitoring checks can identify issues early. For instance, automated checks can scan the code for vulnerabilities or standards violations. If issues are found, the build can be halted automatically, allowing developers to address the problems promptly.

• Support team monitoring 
  
  Support always needs to know what’s going on with the servers and other things. DevOps provides dashboards that show if everything is running smoothly. And if something goes wrong, the team gets a heads-up right away so they can jump in and make things better for the users.

• Accessibility monitoring 
  
  DevOps wants everyone to be able to use the apps, no matter what. So, they have tools that check if it’s easy to use, primarily for people with disabilities. If they find any issues, the team fixes them to make the app more inclusive.

• Alerting 
  
  DevOps watches your apps all the time. If something goes seriously wrong, like a server crashing, alerting sends a text or email. That way, the team knows there’s a problem, and they can fix it as soon as possible.

• Incident response 
  
  When DevOps spots big issues, they don’t waste time. They jump in, fix things up, and take notes on what happened. This helps prevent the same issues from happening again.

User feedback integration

DevOps tools keep an eye on the performance and health of mobile apps in real-time. Plus, they often integrate features for gathering user feedback and analytics, empowering developers to make data-driven decisions for tweaks and updates.

Think of a gaming app company that loves to hear what players have to say. They’ve got feedback forms in their game and use fancy tools like Zendesk or UserVoice. When gamers report problems or share ideas, it’s not ignored. The DevOps sorts it all out and tells the game creators what needs fixing or adding. That way, the game gets better and better, and players keep having a blast.

Security and compliance

DevOps services take on the mobile security concerns tied to app development. This includes sticking to secure coding practices, such as keeping an eye on the validity of the SSL certificate, regularly checking for security gaps, and making sure everything complies with industry regulations and standards.

Collaboration and communication

DevOps as a Service promotes teamwork among dev, operations, and QA teams. It typically includes communication tools and platforms that make collaboration smooth, helping teams work together happily, no matter where they are.

Scalability and resource optimization

Mobile DevOps services tap into cloud infrastructure and other scalable solutions to optimize resources as needed. This ensures that development and testing environments can scale up or down dynamically, supporting the growing needs of mobile app projects.

By getting on board with DevOps as a managed service for mobile development, organizations can conquer the fast-paced and competitive world of mobile apps, where quick development cycles and responsiveness to user feedback can make or break success.

One big thing in implementing DevOps in mobile development is understanding how different mobile platforms actually work behind the scenes. Seasoned DevOps professionals with good expertise surely know all the essential points where the mobile stack differs and needs special care.

Let’s look at the examples of these differences.

Differences in DevOps as a Service for Android, iOS, cross-platform, and mobile web app development

You might go for an app for either Android or iOS — or both individually. Alternatively, you could opt for a cross-platform app to save time and money, avoiding the need to create separate solutions for each platform. As a developer, you might also be exploring the option of a mobile web app or dealing with all these types simultaneously.

Now, what are the key distinctions in the development process for the leading mobile platforms?

Differences in DevOps as a Service for mobile development

As evident, the DevOps as a Service pricing and strategy will differ among mobile app platforms, not to mention the specific stack linked with each. Ensure that your DevOps team possesses hands-on expertise in the precise mobile development approach you choose for your product.

Struggling to set up DevOps for a mobile project?

In the fiercely competitive market of mobile app development, DevOps as a Service presents a potent approach to building high-quality mobile applications. The smooth fusion of development and operations facilitated by DevOps as a Service not only expedites the development cycle but also elevates the overall quality and dependability of mobile apps.

Armed with an understanding of the distinctions among iOS, Android, cross-platform, and web-based mobile apps, businesses can make informed choices in selecting the ideal DevOps as a Service company to drive their mobile app projects to success.

Just 20 years ago, all talk about artificial intelligence was perceived as science fiction. However, the latest achievements in IT and increased computing power have allowed breakthroughs in this area. AI has become a part of our lives, especially in such an important field as healthcare. Despite traditional conservatism in medicine, factors such as the aging population and the COVID-19 pandemic have made the use of AI not only possible but even necessary. Recently, the workload on medical staff has increased drastically, so an intelligent and tireless assistant came in handy. So, what is the future of AI in healthcare? Let’s delve into healthcare trends in 2023 and beyond.

AI technology trends in Healthcare

Among the digital trends in healthcare, it is worth noting the following ones:

1. Telemedicine and IoMT for monitoring patients’ health
2. Surgical robots with built-in AI
3. Application of computer vision to patient care
4. AI as a personal assistant
5. Disease prevention using AI
6. Neural networks for research and diagnostics
7. Handwriting recognition for digitizing medical records
8. AI for administrative tasks

Let’s look at these areas in more detail.

1. Telemedicine and IoMT for monitoring patients’ health

The Internet of Medical Things (IoMT) has given impetus to the development of telemedicine. AI-integrated wearable devices connect to a secure network, allowing doctors to remotely collect patient health data, process it, and send back new recommendations. Moreover, these smart devices can operate relatively autonomously and instantly respond to deviations in a person’s condition, for example, monitoring heart rate or blood pressure. At the slightest suspicion that a patient is in danger, AI will alert a human doctor. Meanwhile, the server-based AI solution can process large volumes of data transmitted from hundreds of thousands of devices simultaneously while applying a personalized approach to monitoring each patient’s health. 

According to the RockHealth.org study, about 80% of Americans accessed care via telemedicine. 46% of respondents reported having a wearable device to track their health condition. [1]

CHECK TIMSPARK’S PROVEN EXPERIENCE IN THE DEVELOPMENT OF TELEMEDICINE APPLICATIONS.

2. Surgical robots with built-in AI

Speaking of smart devices, it is worth mentioning surgical robots — these little assistants to surgeons can perform complex operations with minimal damage to the human body. The doctor still makes decisions during the surgery, but the manipulations and collection of the necessary data are carried out by microrobots. As a result, the patient can recover faster, and the risks of relapse are reduced.

Strategic Market Research reported that the share of robotic surgery in general surgery was 23% in 2022. The surgical robot market is valued at US$5.16 billion in 2021 and is projected to reach US$20.98 billion by 2030. [2]

3. Application of computer vision to patient care

The biggest problem in healthcare is that most people do not follow doctors’ orders. This is especially important when preparing for surgery, during the recovery period, or in the case of a chronic disease when the patient needs to perform certain activities on a schedule. And here, AI comes to the rescue. The widespread application of computer vision makes it possible to monitor how a person is taking prescribed medications.

According to Naturemedicine, about 70% of people with diabetes do not take insulin as prescribed. These results were obtained from an experiment using a wireless AI sensor. [3]

Moreover, artificial intelligence can recognize subtle signs of health problems in patients. It could be facial expressions, gestures, or asymmetries in walking that indicate the person is in pain. Such monitoring can be quite helpful for the elderly since accidental falls due to impaired postural stability can lead to bone fractures and shorten their life. [4]

4. AI as a personal assistant

The effectiveness of treatment directly depends on knowledge of the complete picture of a person’s health status. A virtual AI assistant can help a doctor select personalized therapy based on the patient’s data and accumulated records from millions of similar cases. This approach will be especially effective for the elderly.

The aging population has increased the burden on the medical industry, not only because seniors are getting sick more often but also because older people tend to be lonely, which leads to depression and hypochondria. Artificial intelligence can help here, too: a personal robot assistant will be available 24/7. Chatbots with the NLP function can successfully communicate with a person in their native language and, at the same time, catch markers of the patient’s instability by tone of speech or style of writing. This way, older people won’t feel abandoned, even hundreds of miles from a doctor. After all, AI does not know fatigue and has no prejudices.

The asthma app developed by our team is an example of AI-powered software that can be used as a virtual assistant for patients and medical staff. If you need something for broader use, the IBM Watsonx Assistant medical chatbot may be a good fit. [5]

Market.US predicts that the global healthcare chatbot market will reach US$1168 million by 2032. For reference, in 2022, it was valued at $195.85 million. [6]

5. Disease prevention using AI

In recent years, developed countries have been shifting their focus from treating diseases to preventing them. This issue is especially acute concerning heart stroke, which is still the number 1 killer. Round-the-clock monitoring of a person’s health, activity, and lifestyle can reduce mortality and prevent diseases. This approach became possible with the advent of wearable devices. Moreover, even a small amount of data collected by mobile phone sensors (such as gyroscope, accelerometer, etc.) can be processed by AI to prevent, for example, falls. An uneven gait may indicate cardiovascular disease, rheumatism, or even mental instability.

AI could help identify people who are at around 90% risk of sudden death and who account for more than 25% of all sudden cardiac deaths. [7]

6. Neural networks for research and diagnostics

Prevention of diseases and assistance in patient care are special cases of the Research and Diagnostic field, where AI benefits the most. With machine learning approaches, including neural networks and deep learning, it is possible to derive non-trivial correlations in vast accumulated volumes of data. Artificial intelligence can now do what took research centers years to accomplish in days or even hours.

Of course, it would be unwise to exclude humans from this field: AI may discover an interesting relationship between a person’s diet and the risk of heart attacks or detect a suspicious spot on a patient’s X-rays, but the final decision rests with a human professional. Replacing the radiologist with a completely robotic solution risks false negatives, and it is also unethical. If the news is bad, the patient wants to hear it from a sympathetic person, not a soulless machine. Moreover, AI does not have the critical thinking inherent in humans and, therefore, cannot objectively evaluate the result obtained. The latter is essential for self-learning systems: AI cannot understand how to correct the data it is trained on. We all remember how ChatGPT 4 suddenly became dumber [9] after training on publicly available data on the Internet.  

Nevertheless, the help of a superbrain in processing data, finding correlations, and even proposing innovations (for example, developing new drugs or vaccines) is invaluable. Such ready-made services as Microsoft AI Health can be used for these purposes. [10]

McKinsey research shows that AI can be beneficial for discovering new drug compounds. The use of artificial intelligence in the pharmaceutical and medical-product industries could potentially increase their productivity – from 2.6 to 4.5% of annual revenue or from $60 to $110 billion per year. [11]

7. Handwriting recognition for digitizing medical records

Electronic health records (EHR) will no longer surprise anyone. However, there is still quite a large amount of handwritten data that needs to be digitized and classified. AI can help recognize handwritten texts, and its self-learning abilities make it possible to decipher different handwriting of doctors. This doesn’t just apply to old records. Despite global digitalization, sometimes it is more convenient for medical staff to write a treatment plan by hand or even create it verbally using speech recognition services such as AWS HealthScribe. [12]

Future Market Insights states that EHR Software leads the US healthcare solutions market with approximately 63.3% share in 2022. The Electronic Health Records market in the United States is expected to reach $15.3 billion by 2033. [13]

8. AI for administrative tasks

Conveniently making an appointment with a doctor, timely ordering materials and medications, and processing insurance claims take up considerable time for medical personnel and are not always performed optimally. An AI assistant can save valuable human time and complete the above tasks more efficiently.  

Has the doctor’s appointment schedule changed? The virtual assistant can call patients and find another convenient time for everyone or ensure that prosthetists order suitable materials on time. Artificial intelligence can monitor every stage of work and remind those in charge of the necessary steps. When analyzing insurance claims, AI plays a significant role in fraud prevention. Thus, AI-based solutions can improve the efficiency of routine tasks and reduce the number of human errors.

Today, healthcare workers spend up to 70% of their time performing routine administrative tasks. AI could help here by taking over about 50% of administrative tasks. [14]

SEE HOW TIMSPARK IMPLEMENTED A HEALTHCARE DATA MANAGEMENT SOLUTION. 

Overall impact of AI on healthcare and related fields

The use of artificial intelligence is not limited to the above trends. AI is capable of:

• Improving approaches to medical education through personalization and integration with entertainment technologies such as VR/AR;
• Making insurance processes more transparent, which is very important for countries with developed insurance medicine;
• Helping in the development of high technologies and so on.

A McKinsey study [11] found the following impact of AI on healthcare and related fields:

• Artificial intelligence in software engineering can significantly reduce costs and speed up the process, which is extremely important for healthcare tech development.
• With the adoption of AI, supply chains and operations can become more transparent and seamless.
• Most of the tasks of attracting and retaining customers (or patients in the case of healthcare) can be delegated to virtual assistants.
• And we shouldn’t forget the contribution of AI in research and development, especially when we talk about pharmaceuticals and medical products.

According to McKinsey, AI can increase productivity in healthcare from 1.8 to 3.2% of annual revenue, or from $150 to $260 billion per year. [11]

Interested in building your own AI projects?

Would you like to launch your own AI startup but are unsure of success? AI projects, in general, are costly, and considering you’ll have to compete with the likes of Apple, Amazon, and Microsoft, does it make sense to invest in your idea?

Reviewing healthcare technology trends, we at Timspark believe it’s worth a try. Each project has its highlight (the so-called killer feature), and we can focus on it during development. At the same time, ready-made AI services can be integrated into your solution. This approach allows you to bring a product to market and test your idea quickly. As the popularity of the developed solution grows, third-party services may be replaced one by one. Meanwhile, the accumulated user data can be used to train your own AI software.   

Timspark’s professionals with a computer science degree and experience in Python, Go, C++, Java, Rust, or other languages applicable to machine learning will be happy to support you on this challenging journey.

References

1. Consumer adoption of digital health in 2022: Moving at the speed of trust. RockHealth.org, 2023.
2. Top Robotic Surgery Statistics to Follow in 2023. Strategic Market Research, 2023. 
3. Assessment of medication self-administration using artificial intelligence. Nature Medicine, 2021.
4. Falls and Fractures in Older Adults: Causes and Prevention. National Institute of Aging, 2022.
5. IBM Watson Assistant for Health Benefits Data Sheet. IBM, 2018.
6. Healthcare Chatbots Market. Market.US, 2023.
7. Artificial intelligence may help predict – possibly prevent – sudden cardiac death. American Heart Association Resuscitation Science Symposium, 2023.
8. Apple is reportedly developing an AI-powered health coaching service. Apple, 2023.
9. Is ChatGPT getting dumber? Deutsche Welle, 2023.
10. The Microsoft AI for Health program: Solving the world’s biggest health issues, one life at a time. Microsoft, 2023.
11. The economic potential of generative AI: The next productivity frontier. McKinsey & Company, 2023.
12. AWS Announces AWS HealthScribe, a New Generative AI-Powered Service that Automatically Creates Clinical Documentation. Amazon, 2023.
13. USA Electronic Health Records Market Snapshot. Future Market Insights, 2023.
14. Transforming healthcare with AI: The impact on the workforce and organizations. McKinsey & Company, 2020.

 DesignRush, a reputable B2B marketplace that connects businesses with top-tier agencies, has recently released its list of the best software development companies for the month of October. We are thrilled to announce that Timspark has earned a well-deserved place among the industry leaders in this ranking. This recognition acknowledges our commitment to providing high-quality software development services.

At Timspark, we believe in the power of technology to transform businesses and industries. We understand that every project is unique, and our approach reflects this. We work closely with our clients to craft tailored solutions that meet their specific requirements and challenges. From custom software development to cutting-edge applications, our expertise covers a wide spectrum of services designed to empower organizations in various sectors.

Dzmitry Aleinik, our Digital Marketing Manager, expressed his gratitude for this recognition by DesignRush, saying, “Thanks for the recognition, DesignRush! At Timspark, we’re passionate about what we do and are dedicated to providing excellence in the field of software development. It’s always a pleasure to get featured in respectful rankings, which proves that we are on the right track.”

DesignRush’s rankings serve as a valuable resource for businesses seeking trusted partners in the world of technology and software development. We are delighted to be featured among the top companies, and we look forward to continuing our journey of innovation and excellence in the software development industry.

In October 2023, Timspark embarked on a whirlwind adventure through the world of IT and technology, attending four of the most prominent industry events across Europe and the Middle East. Our mission was to connect with innovators, business leaders, and tech enthusiasts, and we’re excited to share our insights and experiences with you.

From IT security in Germany to the startup scene in Belgium, and then onto the dazzling tech extravaganza in Dubai, and finally to the future of fintech and e-commerce in Berlin, we had the opportunity to delve deep into the latest trends and developments in the tech world. Here’s a glimpse of our journey.

1. it-sa Expo&Congress: Nuremberg, Germany 

When: 10 — 12 October, 2023
Where: Nuremberg, Germany

The journey began in Nuremberg, Germany, at the it-sa Expo & Congress, known as the “Home of IT Security.” This event was a fantastic opportunity to delve into the ever-evolving world of cybersecurity. Timspark showcased the best strategies in management and technology designed to help businesses fend off cyber threats successfully.

Over three days, our team engaged in intense networking established new connections and exchanged insights and industry news with like-minded professionals. Our Regional Business Director, Olga Karpova, described the atmosphere as “highly intensive,” with everyone focused on sharing their experiences and knowledge.

“The conversations were happening in the language of technologies – Golang, Rust, AWS, and Azure,” added Alex Velesnitski, our Chief Technology Officer. This event reinforced the importance of constant vigilance in the ever-changing landscape of IT security.

2. Leuven Slush’D 2023: Leuven, Belgium

When: 12 October, 2023
Where: Leuven, Belgium

Leuven Slush’D 2023 was our next stop, taking us to the heart of the European startup scene in Belgium. With 257 startups, 135 investors, and 161 ambitious young minds in attendance, the event was buzzing with innovation. Konstantin Kariapin, our VP of Business Development, represented Timspark at this exciting gathering.

As we bid farewell to Leuven, we expressed our eagerness to attend similar events in Helsinki the following month. The event underlined the importance of supporting the startup ecosystem and nurturing young entrepreneurs, a cause close to our hearts.

3. Gitex Global: Dubai, UAE

When: 15 — 20 October, 2023
Where: Dubai, UAE

Our journey continued with a dramatic shift in scenery, taking us from the heart of Europe to the bustling metropolis of Dubai. Gitex Global, the “Largest Tech & Startup Show in the World,” is a testament to the UAE’s commitment to technology and innovation. As a dynamic team passionate about technology and innovation, we were excited to be a part of Gitex Global’s 43rd edition.

This event marked the convergence of tech powerhouses and groundbreaking startups, spanning areas such as AI, Cybersecurity, Mobility, and Sustainable Tech. It provided a platform to explore AI’s real-world applications and discover the latest technological advancements.

Timspark made its presence felt at this colossal event, and we invited attendees to book meetings with key team members, including Pavel Gavrilenko, Konstantin Kariapin, Alex Velesnitski, and Samuel Krendel. The event allowed us to immerse ourselves in the power of AI solutions and strengthen our commitment to advancing the world of technology.

4. Seamless Europe 2023: Berlin, Germany

When: 18 — 19 October, 2023
Where: Berlin, Germany

Our journey came to an inspiring conclusion in Berlin, Germany, at the Seamless Europe 2023 event. Here, we had the opportunity to join innovators, business leaders, and entrepreneurs shaping the future of fintech, retail, and e-commerce.

Throughout the event, our team, including Hanna Strashynskaya, our Chief Strategy & Marketing Officer and Olga Karpova, our Regional Business Director in Europe, conducted over 30 meetings, further strengthening our connections in the world of payments, fintech, retail, e-commerce, and delivery.

While we couldn’t meet with everyone we had discussions with, we encouraged attendees to reach out to us and explore exciting opportunities at Timspark. The event was a testament to the collaborative spirit of the tech world, where sharing ideas and forging partnerships is key to innovation.

In Conclusion

Timspark’s journey through these four remarkable IT events was a testament to staying at the forefront of the technology landscape. We gained valuable insights, made meaningful connections, and explored the latest trends and innovations in the industry. As we return from this exhilarating journey, we look forward to leveraging these experiences to drive our technological advancement and innovation mission. Stay tuned for more updates and innovations from us as we continue to push the boundaries of software development and explore new horizons in the IT world.

At Timspark, we understand that staying at the forefront of software development and deployment processes is not merely a choice but our go-to strategy. We have gathered two specialists in the field to shed light on the future of DevOps tools and which solutions are genuinely effective. Our guest and developer advocate at Upbound, Viktor Francis, and Timspark’s leading DevOps expert, Mikhail Shayunov, bring a wealth of experience and share their thoughts on the tools that are shaping the future of software development, deployment, and operational excellence. 

Running databases in Kubernetes — what are the pros and cons?

Mikhail:

Let’s kick off with a burning question to warm up the conversation. It is our task in the current project, and we’ve had a lot of discussions today with the team. Running databases in Kubernetes — what are the pros and cons?

Viktor:

The best option is not to run databases at all and opt for managed ones. Just use a database service from your favorite cloud provider, like AWS, Google Cloud, or Azure. Whatever works. Cloud Native Postgres is actually one of the best options, to my mind.

If you don’t have to run a database, simply do not bother with that. Yet, if you want to manage it yourself, Kubernetes becomes part of the conversation. Kubernetes is the baseline upon which all the cloud vendors build their next generation of projects. Now, there are downsides to running a database on Kubernetes. And the main ones are usually two. 

First, databases are typically managed by database administrators. And they might not be sufficiently familiar with Kubernetes. And when I say familiar enough, I don’t mean, ‘Hey, I played with Kubernetes for a week or a couple of weeks.’ I mean, you need experience of running Kubernetes in production. So, the downside is that the person who will manage that database does not have production experience with Kubernetes itself. 

The bigger downside is that many databases were neither designed, nor rewritten, nor redesigned to run in Kubernetes. Many of the databases were a thing running for 20 years in virtual machines or bare metal. We learned how to package it in a container image. We learned how to write a docker file. Just run the same thing in Kubernetes… and then we have a miserable failure. That does not work straightforwardly, because Kubernetes primitives do not have everything required to run a database. You need to create your custom resource definitions and controllers; when I say you, I mean a vendor managing that database project.

So, that’s really a huge problem that many databases were not adopted to run appropriately in Kubernetes. An excellent example of something that is adopted would be PostgreSQL. PostgreSQL has good controllers and good customer service definitions that allow people to manage it truly in a way that is designed to manage something in Kubernetes, like cloud native Postgres. On the other hand, running an Oracle database on Kubernetes is just senseless. Simply because, as far as I know, nobody ever bothered to design how it should run correctly on Kubernetes. 

Argo CD workflows for Kubernetes

Mikhail:
Let’s talk about Argo CD workflows for Kubernetes. Can it replace previously popular CI/CD tools, in your opinion?

Viktor:

Absolutely no. It cannot come even close to replacing them. Not even previously popular CI/CD tools — it cannot replace CI/CD tools, period. 

And the reason is very simple. Argos CD ensures that the data from GitHub is synchronized with the data in some Kubernetes clusters. So, it’s about synchronization, or what people in the past would call deployments. 

Now, what is CI/CD? Continuous integration, or continuous delivery, or continuous deployment? It’s a whole process from the beginning to the end.

With CI/CD, which I prefer to call pipelines precisely because people are getting confused today, we build images, run tests, and perform security scanning, to name a few. We have dozens of different steps in a pipeline required for our code until it gets to production. And one or two of them would be the deployment itself. So, the correct answer is Argo CD can replace a part of the CI/CD process, which is currently performed by pipeline tools like Jenkins or GitHub. 

Deploying solutions with Cloud CI or Jenkins

Mikhail:

Yet, we can use Cloud CI or Jenkins for deploying our solution to Kubernetes without running any additional services.

Viktor:

Let’s say that you deployed your application right now, and you released it. And let’s say for the sake of argument that three hours from now, the process will fail. What happens after that? The actual state changed and compared to the desired state, and there is nothing that will reconcile those two. So the question to ask here is: do you want to have continuous drift detection and reconciliation and want it to repeat continuously? And how do you know the desired state, not only the actual one?

We never use one tool — we use one tool to orchestrate pipelines. And that orchestration involves many, many different tools. You’re not building with Jenkins. You’re telling Jenkins to execute, and I’m using Jenkins as an example. Pipelines are orchestrating the whole process. And using different tools to orchestrate those processes. From that perspective, we are not changing our pipelines’ work. We are just orchestrating the execution of tasks differently. Instead of executing Kubernetes in the pipeline, we are pushing the changes to Git.

And apart from drift detection, reconciliation, and security, I have another benefit. As a human, I can check for myself what is the desired state. Many people say we can consider Git as the source of truth. I think that’s wrong because the source of truth is only your system and is never what you want. But Git becomes your source of information. 

Mikhail:

So why is Argo CD becoming so popular right now? Do you personally use it?

Viktor:

I use it all the time. I mean, I use both Argo CD and Flux, sometimes even kapp-controller. Thus, I have certain guarantees that the state I have defined in Git is going to be the state that is somewhere else. But I don’t have that guarantee if I use pipelines. And the reason is relatively simple.

Pipelines are performing one short action, meaning when I push something to Git, certain actions will be performed, and they can be performed alongside other things. For instance, deployment with Helm. Once we execute these commands, we are going to get the exit code. And unless I get the exit code and then the notification, I do have a guarantee of a desired state from the pipelines. The problem is that those guarantees stop the second later. Whenever any changes happen to my system, it starts drifting. The application might fail five seconds later, and it’s not running anymore, or a whole zone went down. What GitOps tools do is drift detection so that reconciliation continues.

So with pipelines, I’m getting a guarantee something will happen when I tell it to happen, while with the GitOps tools I have guarantees we will continuously maintain the actual desired state, which is the same as anywhere else. We can constantly monitor those two states, and if there is a drift, we will reconcile one with the other.

In some cases, you do want things to happen once; in other cases, you want something to happen continuously. For instance, running tests is typically performed with pipelines, as you run them once and get the results. I’m excluding the case of flaky tests that are randomly failing. But GitHub is a good thing for something that should be maintained continuously in your system. Your infrastructure, applications, and services should be in the desired state 100% of the time. And the only way to accomplish that is to ensure that that drift is being searched for all the time.

Another reason why people like Argo CD, Flux, and other similar tools is security. When we use pipelines, we need to open access to our system so the pipeline can enter and change its state. If I’m using Kubernetes or GitHub Actions, the only way to change the state of my Kubernetes cluster is by opening the port. Surely, you will have credential security stored, but realistically, when you open the port, you allow other people, tools, or processes to potentially enter and threaten the system.

However, with GitOps, no external entity comes to your cluster and modifies it. The processes are running inside that cluster. They are very efficient and do not need much memory and high CPU usage.

So, apart from being primarily implemented for drift detection reconciliation, security is the reason for using Argo CD. It’s pulling information from Git while sitting in my system and performing changes to that very system.

Mikhail:

Let’s talk about AI for Kubernetes and whether you think it has potential now.

Victor:

So, it depends on how we define potential. If you define potential as the future tense, AI will certainly play a crucially important role in the future. I have zero doubt about it. AI will completely change how we as humans operate on many different levels, and that includes Kubernetes.

But does it provide value today? I would say a little bit. And that will probably sound strange because if you Google or go to a conference, you will see AI everywhere. We are on a hype train right now. Everybody talks about AI. ‘Let’s do something with it! Joe, can you please set up something over the weekend?’ And in 99% of the cases, literally, anybody can come up with a similar solution. Let’s say create a wrapper code that sends a message to ChatGPT API, gets the message back, and then shows you on the screen what the response is. Those solutions can be replaced with cURL. To make it clear, I’m not saying the same thing for AI in general. 

Regarding Kubernetes, there is a low impact and no investment in AI right now, particularly in this field. The majority of AI solutions for Kubernetes are not groundbreaking. They are basic and not secure. This happens for two interconnected reasons.

First, as an industry, we didn’t have enough time to come up with thorough solutions. Most people found out the importance of AI less than a year ago. Until last year, the buzzword for possible investment was ‘security’. Now, it’s about AI. Roughly speaking, these are mostly ad hoc solutions or even rapid prototyping, so you can put an AI sticker, market it, or probably get investment.

And second, the companies aspiring to come up with solutions for Kubernetes do not have enough ML or AI experts in their organization.

In the context of potential, the main area of AI must be the management itself. What I want to see within the scope of Kubernetes is a tool to fix my problems. I don’t want the tool to depress me and tell me, “Hey, this is wrong’. I already know it’s wrong. Can you please fix it for me? Sometime in the future, we will see AI intelligent enough to change your resources, scale them up and down to fix problems, and do whatever we as humans are doing, but implement it as a machine.

Mikhail:
Are there any not-obvious but must-have and must-learn DevOps tools you would recommend delving into today? Can you name a few?

Victor:

First tools are never good, so keep a hand on what comes next. I would say I’m fortunate. A significant part of my time is spent discovering things that almost nobody else knows about and figuring out what to do with them — testing them, researching, and delivering them to the public.

I strongly recommend Timoni. It is one of those tools that is relatively new, started maybe half a year ago. With Timoni, one can define Kubernetes manifest using CUE as a configuration language.

Essentially, it replaces Helm, and personally, I consider Helm the worst possible option anybody can use to define Kubernetes manifest. And this is an ongoing problem — we never thought about how we can manage the Kubernetes manifest. 

Another tool I really like and which is relatively new is Port. It’s a front-end part of what people would call an internal developer platform. Right now, we have backstage as the most popular and finally adopted solution. Backstage is great, mainly because it shows us what we should do, but it fails miserably because it’s too complicated and tedious and requires too many people to operate. Port is providing that front-end part of the platform in a much more elegant way. 

Mikhail: What tools for improving security in your solutions on Kubernetes do you use?

Victor:

Github. I’m kidding, of course. First of all, many of the things I’m using are not even security tools, but more like practices. For instance, there are a lot of tools that scan your container images, which is great. You should be doing that for security purposes. But designing them right from the start is even more important than scanning your container images. And that brings me to ChainGuard. What the tool does essentially is give out secure images with zero vulnerabilities. 

And they provide images that are building daily in the first place. A base image might have zero vulnerabilities today, but then it will have vulnerabilities tomorrow, and ChainGuard prevents this.

There are a couple of solutions coming. Komodor, for example, is doing scanning of the cluster itself. The tool has already been released, and to me, it is extremely interesting. It performs dynamic scanning of your data instead of a static one. This helps identify vulnerabilities more effectively.

When scanning is concerned, my assumptions are tools will be moving to runtime scanning. They will get the context of something running in the system and then get the information about vulnerabilities. When we have the context, those tools can decide, within this context, whether it is truly a vulnerability affecting you or a CVE.

This allows you to use Kernel extensions, and by extending Kernel, you can, among many other things, contribute a lot to security simply because you are able to control Kernel processes without disrupting the system.

Mikhail:
Thank you so much. All worth checking out. And what about backup and disaster recovery for Kubernetes? Do you know any tools for this?

Victor:
There are two things you need to think about — restoration of the disaster recovery data and the definition of the system. By data, I mean databases. The disaster recovery of databases in Kubernetes does not differ significantly from restoring data from databases running elsewhere. You have a database and a specific way to back it up.

For everything else in a database that is not data, and now I’m not joking, that’s GitOps. Because if you have accurately defined the desired state of the system in Git, and let’s say that I destroy the whole cluster, then create a new cluster and still restore it in Git.

The only exception for using GitOps is data. And, of course, we should be running data in at least three data centers that are geographically close to each other but with separate electricity, network, and everything. So that we can spread the cluster across three zones and three data centers, so the chances for recovery are higher.

Mikhail:
And does it make sense to use Kubernetes Cluster Federation for high availability? If you want to run your application in different data centers that are not geographically collocated.

Victor:

Yes, in this case, you need multiple clusters, with or without Cluster Federation. A minimal number of companies truly need it, though — companies like Adobe or Netflix. But for a vast majority of companies, I would say ‘no.’ Simply because it doesn’t work well enough, and it proves to be more of a trouble than a really useful solution. Still, we do not have a decent way to spread Kubernetes cluster one way or another across multiple regions. And by regions, I mean data centers thousands of kilometers apart.

Mikhail:

So, in this case, we can say that the Kubernetes cluster is not for huge architecture and huge infrastructure projects.

Victor:

Quite the opposite. Kubernetes came from Borg, and there is nothing bigger than Borg. Massive companies are using Kubernetes, we just have challenges running data across different continents.

And that has nothing to do with Kubernetes. The reason why we do not deploy the same Kubernetes cluster across nodes in multiple regions is latency. And latency is the problem of physics. That nothing can travel faster than the speed of light.

Mikhail:
Let’s create a list of tools and services that we should provide for the support team in production so that they do not need to connect to the cluster.

Victor:

Essentially, you need two things. First, you need to be able to define the desired state of your deployment services. The most commonly used way to do that is GitOps tools, Argo CD, Flux, or kapp-controller. You’re defining whatever you want in Git, and they will get the information synchronized.

And the second thing you need is an observability-related tool. And I’m using observability in a very generic term, meaning that whatever you need to observe in any form or way. This equally applies even if you use kapp-controller. You need metrics, logs, and traces. Some tools will be able to store all three of those, like Elasticsearch. The problem is these are very different types of data. And if you try to store these in one place, you will not be able to use specific tools, only generic ones like Elasticsearch. And they become very inefficient, using much more memory CPU and being much slower. The alternative is using separate tools for all three of those: Prometheus for metrics, Loki for logs (I personally prefer it), and Grafana Tempo or Jaeger for traces.

We have never had that before. Now we finally have a standard that tools do not matter anymore. And that’s awesome.