In basically every modern software organization, building software is not just a matter of writing code – it’s a matter of testing it to ensure it works properly, a matter of creating artifacts out of it that can be used by the end customers, and a matter of deploying them to a customer-accessible location for these customers to be able to actually use it.
The term ‘cloud native’ has become a much-used buzz phrase in the software industry over the last decade. But what does cloud-native mean? The Cloud Native Computing Foundation’s official definition is: From this definition, we can differentiate between cloud-native systems and monoliths which are a single service run on a continuously available server. Like Amazon’s AWS or Google Azure, large cloud providers can run serverless and cloud-native systems.
Juju re-imagines the world of operating software securely, reliably, and at scale. Juju realizes the promise of model-driven operations. Excellent observability is undeniably a key ingredient for operating software well, which is why the Charmed Operator ecosystem has long provided operators the ability to run a variety of open source monitoring software. We collectively refer to these operators as the Logs, Metrics, and Alerts (LMA) stack.
For you, one or more of these statements (and / or challenges) likely apply to you, and the organization for which you work. Which of these are you hearing or saying? Splunk can help you with these in many ways. Today, I am highlighting one way to address many of these statements, specifically with the Content Pack for Splunk Observability Cloud.
With the demand to meet service level agreements (SLAs), any on-call SRE can tell you that incidents always happen at the wrong time. Things break when you least expect them to (on a date, about to beat a new level in a video game, pizza delivery just arrived, asleep at 3am). During these inopportune moments, you want to make sure it's easy to get the data you need, no matter which device is nearby.
An application’s success depends on many factors. One of the most crucial is how it performs when actual users interact with it. The chances are that even if you properly prepare your entire software development strategy, problems will occur at some point or another.
Observability has gained a lot of momentum and is now rightly a central component of the microservices landscape: It’s an important part of the cloud native world where you may have many microservices deployed on a production Kubernetes cluster, and a need to monitor these microservices keeps rising. In production, quickly finding failures and fixing them is crucial. As the name suggests, observability plays an important role in this failure discovery.
Today, we announced that Honeycomb has raised $50M in Series C funding, in a round led by Insight Partners and joined by all existing investors from our Series B. We’re using this investment to support the growth of our customers and community, ensure the benefits of observability can be realized by all engineering teams, and expand the ways we can better serve you.
Log observability and monitoring are terms often used interchangeably, but really they describe two approaches to solving and understanding different things. Observability refers to the ability to understand the state of a complex system (or series of systems) without needing to make any changes or deploy new code.
