Over the past decade, the software development landscape has shifted dramatically. Long development cycles resulting in big releases are now a thing of the past. Instead, the focus is on delivering value to the customer quickly and efficiently through small releases delivered at a high frequency. This shift is not without its challenges. Increased release velocity means an increased threat to security and reliability. To combat this, teams must collaborate fluidly across the organization.

Consumers and users of applications expect near 100% availability and reliability to work, transact, collaborate, etc. There’s a lot of talk about monitoring the performance of the application itself, but what about the underlying systems and components supporting the app, and in particular the infrastructure it sits on? If any piece of this stack fails, it can negatively impact the user experience, and in turn, your business.

Technology environments are rapidly evolving as organizations look to remain competitive, accelerate innovation and make themselves more agile. But in the process, many of the observers, i.e., stakeholders who track infrastructure and application metrics, are falling behind, unable to monitor and manage modern, cloud-native apps and multi-cloud environments due to the complexity that comes with them.

Back in 2018, AWS first released its Graviton processor—their custom-built 64-bit Arm processor—and followed that with the release of Graviton2 processors just a year later. Now customers running ECS and EKS on EC2 can choose between X86 and ARM64 depending on which processor best fits their application workload.

If you’re responsible for a significant number of Windows servers, you already understand the importance of being aware of the health and security of your environment. Unfortunately, you’re probably also aware of the tremendous amount of effort and resources required to monitor your Windows environment. Let’s take a look into why and how you should be closely monitoring your Windows server environments from a security perspective.

Every company is a software company and every company wants to get better at it. That’s the reason we built Software Development Optimization or SDO. SDO helps you track siloed data across the DevOps toolchain. It normalizes and correlates data, provides you with DORA’s 4 key metrics and gives you deep insights into the velocity and quality of delivery across services and teams.

Amazon Elastic Kubernetes Service, or EKS, is a managed Kubernetes service. That means that Amazon Web Services (AWS) handles some of the deployment and management tasks for users. But the fact that EKS is a managed service doesn’t mean that AWS manages all administrative tasks. One key management task that isn’t fully covered as part of EKS is monitoring.

An often overlooked aspect of a company’s journey to the cloud is cost visibility. While the single number delivered by the cloud provider on a monthly invoice is straightforward, understanding where this number comes from is often more tricky. Fortunately, this task can be facilitated through the usage of various cost monitoring tools available on the market, coming from both third-party companies and the cloud providers themselves.

When you’re planning an application performance monitoring (APM) strategy, collecting metrics from storage services like Amazon S3 may not seem like a priority. After all, part of the point of object storage is that applications can read and write from storage buckets seamlessly, with minimal configuration and overhead. Unlike databases or file systems, storage buckets don’t require complex configurations that could lead to performance issues.

I have always found data collection to be a fascinating area of work at Sumo Logic. Collecting data is a critical first step for all the solutions we develop for our customers. After all, to observe the health and performance of your applications, you must first collect all relevant data. It's also an area that has seen some significant activities by the open-source community over the years, which is completely changing the landscape of observability as we know it.