Whether you’ve heard of or fully jumped on the DevOps or SRE bandwagon, you may have also wondered how the two relate. What’s the difference? Are they really just different ways of looking at the same problem? The term DevOps hit the market first, but SRE wasn’t too far behind. And though they have different origin stories, they both focus on autonomy, automation, and iteration. So why do these paradigms exist? And why do we need both? Let’s look at this further.

The latest version of the Splunk Operator builds upon the release we made last year with a whole host of new features and fixes. We like Kubernetes for Splunk since it allows us to automate away a lot of the Splunk Administrative toil needed to set up and run distributed environments. It also brings a resiliency and ease of scale to our heavy-lifting components like Search Heads and Indexer Clusters.

We’ve already outlined why API performance matters and what aspects of APIs to test, but what is the difference between API testing and monitoring? As with most things, context matters. The use cases for testing and monitoring are different because the objectives are different. The ultimate goal is to verify that your APIs are functioning properly, but staging environments vary significantly from production environments.

Simple questions can be overwhelming and not knowing the answer after a mouse click is no longer an option: Sustainability is top of mind for organizations across all verticals and Splunk can help with the power of data. Our upcoming Sustainability Toolkit based on the Splunk platform equips organizations with capabilities to gain deep insights into their carbon footprint and as such empowers them to take the necessary actions towards their carbon neutrality goals.

Digital businesses are making a radical change in the way they build and deliver software. Gone are the days of apps that rely solely on in-house tools. Rather, today’s apps are increasingly dependent on external APIs and third-party app providers (which, in turn, are reliant on other APIs and apps). While this type of modularity allows for product flexibility and rapid development, it can be difficult to address any issues that arise.

Managing the complexities of today’s cloud native infrastructure has resulted in the increased need for observability. As cloud adoption continues to grow, the need to deliver a better customer experience, scale efficiently and increase momentum on innovation has never been more important. For many organizations to carry out these principles, two technologies are helping organizations deliver on these goals faster: Monitoring-as-Code and Infrastructure-as-Code.

We are excited to announce that Splunk Cloud Platform is moving to next generation AWS Graviton2 processor hardware to help enable enhanced performance for customers who choose AWS as a provider. This begins a phased transition of our Splunk Cloud Platform indexer tier in a move that will help Splunk operate more efficiently and provide customers with the cutting edge in processing technology.

I’m sure many of you have heard of our Machine Learning Toolkit (MLTK) app and may even have played around with it. Some of you might actually have production workloads that rely on MLTK without being aware of it, such as predictive analytics in Splunk IT Service Intelligence (ITSI) or MLTK searches in Splunk Enterprise Security.

In a recent episode of the Cloud Happens podcast, Archana Venkatraman, Associate Research Director in Cloud Data Management at IDC Europe talks about how the cloud isn’t a destination. It’s a continuum; a journey. In this blog, we explore that idea a bit more and dive into what really encapsulates a cloud experience. How can modern enterprises benefit from their cloud journey to solve the most gnarly data challenges to unlock innovation, enhance security, and drive resilience.

In previous posts we covered why it’s important to monitor APIs and how to monitor and validate data from APIs. In this post we’ll focus on a simple but key feature that helps Splunk Synthetic Monitoring users create robust checks for availability, response time, and multi-step processes: Request Headers