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AWS Fault Injection Simulator (FIS) offers a solid foundation for chaos experiments in AWS environments, but its reach stops at AWS. Steadybit enhances this by supporting hybrid and multi-cloud setups, offering intuitive orchestration, custom experiment design, and enterprise-level features for deeper resilience testing across diverse infrastructures.

Apache Kafka is a cornerstone for building scalable event-driven systems, but its complexity can lead to cascading failures during disruptions. Steadybit's new Kafka extension empowers teams to simulate real-world scenarios, uncover vulnerabilities, and validate the resilience of their Kafka clusters under stress.

Building a culture of resiliency is as important as having a resilient system. Embracing Chaos Engineering at every level fosters a proactive, collaborative environment where failures turn into learning opportunities.

Chaos Engineering involves introducing controlled disruptions into systems to identify vulnerabilities and improve overall resilience. Site Reliability Engineers (SREs) lead this process, focusing on monitoring, integrating chaos experiments into CI/CD pipelines, and ensuring experiments are carefully controlled and measured to avoid unintended real-world impacts.

When Black Friday hits, your system needs to be ready for anything. These five chaos engineering experiments will help you identify weak points and fortify your e-commerce infrastructure to handle the pressure of peak traffic.

Knowledge sharing is key when implementing Chaos Engineering in your organization, and Steadybit's new experiment templates make this even simpler. This blog explores how to maintain synchronized experiment templates across multiple on-premise instances using hub connections and API-based methods.

Chaos engineering strengthens your systems by proactively testing their resilience through controlled failures. It prepares your infrastructure for real-world challenges, ensuring reliability and uptime even under stress.

Chaos engineering strengthens systems by introducing controlled failures to expose weak points. As distributed systems grow more complex, this practice becomes essential to ensuring resilience and minimizing unplanned outages.

For large enterprises, reliability is everything. Whether you run an e-commerce platform or manage a Fortune 500 infrastructure, downtime impacts revenue and damages your reputation. Steadybit makes chaos engineering practical, running controlled experiments to push systems to their limits, so you can find weaknesses before they cause trouble.

Chaos engineering helps small teams proactively test and improve software resilience by simulating real-world failures. With Steadybit, you can automate experiments and continuously strengthen your system without overwhelming your team.

A fast application startup enhances user experience by reducing waiting times and minimizing downtime during deployments or failures. This guide explores strategies to achieve consistently quick startups.

Steadybit's new Grafana extension allows you to test alert rules using chaos engineering. This proactive approach ensures alerts are both reliable and resilient.

Chaos engineering is a powerful tool to uncover system vulnerabilities, but it requires ethical practices to protect user trust and data privacy. This article breaks down five essential principles for implementing chaos engineering responsibly, offering practical steps to safeguard system integrity and transparency.

Microservices and APIs bring flexibility but also create hidden challenges, especially around service dependencies. Discover how to manage these dependencies effectively and prevent performance issues before they impact your users.

Kubernetes resilience goes beyond technology—it's about ensuring your services can handle anything without missing a beat. Learn how to safeguard your deployments and minimize downtime.

Introducing Steadybit’s Experiment Templates—customizable, reusable tools that simplify chaos experiments and save time. Focus on improving system reliability, not setup.

Strong access control is essential for running chaos experiments without disrupting critical systems. Steadybit’s Role-Based Access Control ensures tests stay focused and controlled.

Balancing cloud costs with system reliability is a challenge. Discover how chaos engineering can optimize your cloud environment, saving costs and improving performance.

DORA is set to reshape digital risk management by 2025, with a focus on resilience testing. Learn how Steadybit’s platform can help you meet DORA’s requirements and build stronger systems.

Big news: Steadybit now integrates with LoadRunner Enterprise, pushing the boundaries of chaos and performance testing. Together, we're creating more resilient digital environments.

Steadybit empowers you to run chaos experiments like dependency failures, resource manipulation, and network disruption. Discover how to simulate these real-world conditions to enhance system resilience.

Meet Advice, Steadybit’s newest tool for navigating chaos engineering. It’s customizable, open-source, and always ready to help you fine-tune your system’s reliability.

Chaos engineering not only strengthens systems but also equips teams to handle failures with confidence. By simulating real-world disruptions, it prepares both technology and the people behind it for the unexpected.

This blog is about why chaos engineering is your go-to move in 2024. It's not just about keeping up with tech trends; it's about building systems tough enough to roll with the punches. Let's dive into how chaos engineering can be your company's ticket to staying resilient and reliable when things get shaky.

Reliability is the cornerstone of user satisfaction in today's world. At Steadybit, we understand the critical nature of this reliability, especially in Kubernetes clusters widely adopted across organizations. We're excited to announce our latest suite of enhancements, designed to empower users to detect and remediate potential risks in their Kubernetes environments proactively.

Scalability is a crucial concern for any engineering team. As your operations grow, so does the complexity of your systems. How can you ensure robustness and reliability during this vital phase? The answer is Chaos Engineering. This blog delves into why this methodology is a game-changer for engineering leaders guiding their teams through scale.

We're taking an exciting step into the world of open-source software. The code for Steadybit's Chaos Engineering attacks is now publicly available, offering a new level of transparency and collaboration. But what does this mean for developers and the broader community? Let's delve in.

Two years have passed since my first blog post about Retries with resilience4j, where I promised a second post about Circuit Breakers. There it is!

Chaos Engineering helps businesses ensure system resilience by intentionally introducing failures and observing how systems respond. Learn how tools like Steadybit simplify this process for continuous improvement.

The holiday season is a high-stakes period for e-commerce businesses, with traffic and sales often surging to yearly highs. While this presents a significant revenue opportunity, it also puts your systems under immense strain. In this environment, preparing with Chaos Engineering is not just an advantage; it's a necessity. Here's why.

In this blog post, we'll take a look at how your team can effectively incorporate Chaos Engineering principles into your organization using the Steadybit platform.

By utilizing Steadybit for Chaos Engineering, you not only improve the reliability of your system but also enhance your business's financial resilience and overall success.

Improving your system's reliability can be challenging. Initially, you are looking at a large pile of infrastructure components from a dozen teams. They are all somehow connected, and every piece will fail eventually. While you can use Chaos Engineering to reveal the impact of each failure, you can't predict when a failure will happen. This makes it hard to know where to start and where to continue to keep getting the most value from Chaos Engineering. Also, once you have identified the first findings with Chaos Engineering, you need to check what other components suffer from similar issues.

We’re excited to introduce Experiment Schedules, designed for simplicity and flexibility to revolutionize how you manage experimental workflows.

We're super excited to share some insights from a recent episode of the SMC Journal podcast featuring none other than our co-founder and CEO, Benjamin Wilms. A deep dive into the realm of performance engineering, this episode unpacks the world of resilience testing, chaos engineering, and, of course, the role Steadybit is playing in all this.

In our most recent webinar, Tailor Chaos Engineering to Scale Your Reliability Journey, our Product Manager Manuel Gerding, discussed how chaos engineering can enhance a system's reliability. The session featured riveting insights on ways to conduct chaos engineering more effortlessly, while demonstrating Steadybit's robust approach to this practice.

Discover chaos engineering’s benefits by introducing controlled failures to reveal system weaknesses. This approach improves resilience, identifies vulnerabilities, and promotes continuous improvement for robust systems.

Learn how to integrate Chaos Engineering into your GitOps practices using Steadybit. We'll shortly cover in this blog post what GitOps is, followed by where you can benefit from integrating Chaos Engineering. Finally, we integrate Chaos Engineering hands-on using the Steadybit CLI and a GitHub action.

Why purple and blue are the new green and yellow: learn how colours have the power to influence our perceptions and emotions, and how the wrong colour can make or break a product. Let's channel our inner Bob Ross and paint some chaos together and see how this small change can make a big difference in the resilience of our systems.

This article demonstrates how to implement an attack to inject failures for AWS Lambda and integrate it into Steadybit.

This article demonstrates how to implement an attack to inject failures for AWS Lambda and integrate it into Steadybit.

This article demonstrates how to implement a discovery for AWS Lambda. This is a prerequisite to inject failures into those.

We have released our integration into Datadog recently. Within Datadog, the Steadybit integration is now available and can be installed. The integration includes a ready-to-go dashboard. Steadybit experiment events can also be inspected in the Datadog event views.

You can extend Steadybit to make it a perfect match for your systems. We already provide some OSS extensions. This article will give you an overview of the available extension points.

Chaos Engineering has been around for several years, and the practice has evolved. Within this post, we will look at past and modern interpretations, industry opinions and what we believe to be critical for you to leverage the practice to reach your goals.

The last blog post taught you how to set up a query language lexer and parser using ANTLR. This post will cover making this setup accessible in a user interface.

In this second part of the query language blog series, we look closely at the implementation of the lexer and parser.

This article will look closely at continuous verification with Steadybit through resilience testing and how it helped us internally.

When managing complex environments it's important to have powerful tools available to keep control. Now, Steadybit enhances the way how to filter targets by introducing the Query Language.

Steadybit wants to change the way outages are handled. Instead of reacting, Steadybit strives for a proactive approach integrated into the development cycle of modern applications.

If you are also wondering how to shift left Resilience and Chaos Engineering to Developers, you are reading the right article.

Since we build software nowadays differently than a couple of years ago, performance testing alone isn't sufficient anymore. Learn how to profit from the synergy of performance testing and Chaos Engineering - a symbiosis of k6 and Steadybit.

If you run chaos experiments, you certainly want to see how these experiments play out in your monitoring tools - even more so when you run experiments.

Is chaos engineering for experts only? No! Learn how we imagine opening up chaos and resilience engineering to wider audiences through declared and reusable expectations!

Writing resilience tests with the Steadybit Testcontainers library makes it easy to validate and strengthen the fault tolerance of your application in a controlled environment. While these tests effectively prevent regressions and catch issues early, they complement rather than replace Chaos Engineering GameDays, which help teams rehearse and respond to complex, real-world incidents across distributed systems.

Validating resource limits in Kubernetes is crucial to ensuring that your applications behave as expected under load and do not impact other pods on the same node. Steadybit provides the ability to simulate increased resource usage, allowing teams to verify and fine-tune these limits for improved resilience and stability.

Testing DNS failures with tools like Steadybit helps identify vulnerabilities in how applications handle DNS disruptions. This proactive approach ensures systems remain resilient, even when DNS services are compromised.

A GameDay is a structured, collaborative exercise where teams test their systems for weaknesses in a safe, exploratory environment, aiming to improve resilience. These exercises reveal hidden knowledge within the team and identify critical weak points. Running GameDays regularly ensures ongoing system reliability and boosts confidence. From crafting meaningful experiments to executing them with minimal preparation, teams gain valuable insights and create more resilient systems over time.

Resilience4j is a powerful tool for building fault-tolerant applications. This post explores how to implement and test its retry mechanism, demonstrating the benefits of fallback methods and showing how to evaluate real-world performance impacts using Steadybit to ensure reliability under load.

Integrating New Relic with Steadybit allows you to monitor and verify the impact of your chaos experiments in real-time, directly within your existing observability setup. This post walks you through configuring the "State Check (via REST API)" feature so you can track New Relic events during experiments, enhancing control and insight into your system's response.

Chaos Engineering has evolved from a radical practice to an essential part of building resilient systems. While breaking parts of a system is simple, creating a culture of resilience requires collaborative efforts, continuous learning, and tools that guide teams in assessing risks without hindering progress. The future lies in balancing reliability with development speed and fostering shared knowledge to build transparent, resilient applications.

Liveness probes are vital for ensuring that applications recover automatically when they enter an unhealthy state. This post explains how to set up liveness probes in Kubernetes and use Steadybit to verify their effectiveness through controlled experiments that simulate delays and observe pod restarts, confirming the reliability of these probes.

This post delves into how mental health and team resilience are pivotal for fostering a culture of reliability in tech, especially in Chaos Engineering. Insights from Nora Jones, CEO of Jeli.io, emphasize that building resilient systems goes beyond technical tools—it requires psychological safety, effective communication, and allowing teams to learn and share knowledge collaboratively.

If you have sequential REST calls in your code, how do they behave under slow network conditions? This post demonstrates how to enhance performance by switching to Spring WebFlux for parallel data fetching and validate improvements with Steadybit experiments.

Integrating Prometheus with Steadybit allows you to track real-time metrics during chaos experiments for better insights and control. This post explains how to set up Prometheus as a monitoring integration, configure state checks, and observe alerts directly in Steadybit to enhance your experiments’ effectiveness.

Measuring the steady state of your system is essential for effective Chaos Engineering. This blog post outlines how to assess system resilience through static analysis, dynamic testing, and defining critical metrics. With a user-focused approach, leveraging metrics like response time and business indicators, teams can better understand system health, detect issues faster, and enhance MTTR for greater reliability.

Distributed systems are complex, and Steadybit’s new experiment engine helps test realistic scenarios like DNS failures or container restarts under turbulent conditions. This blog post shows how to set up comprehensive experiments that mimic real incidents to uncover system weaknesses and explore solutions for improved resilience.

Downtime is costly, and Chaos Engineering helps mitigate these risks by exposing weaknesses before they become issues. This post breaks down the cost-benefit analysis of implementing Chaos Engineering, emphasizing that while initial costs and potential disruptions exist, the long-term ROI—like a 92% return in a sample calculation—proves its value for improving system resilience.

Spring Boot’s RestTemplateBuilder defaults can sometimes overlook critical timeout settings, leading to potential reliability issues under network strain. This post explains how to identify and address such gaps using Steadybit for chaos testing, demonstrating how to configure appropriate timeouts to enhance your application’s robustness.

Building a successful, user-centric product is crucial for a startup like Steadybit. This post discusses Steadybit’s journey from its founding vision to refining its product by prioritizing user research, understanding pain points, and balancing engineering speed with system reliability.

This post covers the top three weak points in Kubernetes that can impact service availability: single pod replica counts, missing liveness and readiness probes, and missing resource limits. By using Chaos Engineering, you can simulate turbulent conditions to ensure your cluster can handle real-world failures effectively.

Test whether your exception handling for Spring Boot’s RestTemplate is effective using chaos experiments with Steadybit. This method eliminates the need for cumbersome mock testing or manual interventions.

Cloud services like AWS, Azure, and GCP enable rapid software deployment with on-demand resources that can be more cost-effective than traditional data centers. However, designing for resilience requires understanding key concepts like regions and availability zones, which help applications withstand failures through distributed and isolated infrastructures.

Fast application startup times are crucial for maintaining a low mean time to recovery (MTTR) and supporting continuous deployment without fixed maintenance windows. This post explains how to validate startup performance through automated chaos experiments that ensure new instances become ready within a set timeframe, enhancing reliability and operational predictability.