Kubernetes vs OpenStack is a common dilemma that organisations face when considering the modernisation of their IT infrastructure. Both are well-established open-source technologies for building cloud infrastructure, and both bring tangible benefits, especially when used in combination. Yet, they differ significantly and need to be properly bundled to feel like a fully-integrated solution. What does this mean in practice? Let’s take a look!
In a prior blog post, we discussed the basics of Kubernetes Limits and Requests: they serve an important role to manage resources in cloud environments. In another article in the series, we discussed the Out of Memory kills and CPU throttling that can affect your cluster. But, all in all, Limits and Requests are not silver bullets for CPU management and there are cases where other alternatives might be a better option.
Using Cribl Stream for observability is a given, but what about using Cribl Stream to get MORE from your data? Observability is all about being able to collect, route, store, and search your data. Implementing enrichment with observability provides more context and elevates your ho-hum data to robust information. This is key to faster, more confident decision-making!
It’s ironic, but exceptions happen all the time. We all can relate to these in supply chain operations: the crushed package, the barcode damaged to the point it can’t be decoded, the misplaced or abandoned tote. When these errors occur, what happens? The person who discovers it is responsible for reporting it. How long does that take? Who do they report the incident to? Should they address it themselves?
Centralized logging is a critical component of observability into modern infrastructure and applications. Without it, it can be difficult to diagnose problems and understand user journeys—leaving engineers blind to production incidents or interrupted customer experiences. Alternatively, when the right engineers can access the right log data at the right time, they can quickly gain a better understanding of how their services are performing and troubleshoot problems faster.
It may be counterintuitive to tackle a problem without knowing exactly what the problem is, but an incident commander often does just that. In fact Rob Schnepp—founding partner at Blackrock 3, an Alameda, California-based incident management consulting group—says identifying the root cause of an incident is typically secondary to addressing the symptoms.
ITOps professionals know that their AI and automation goals can only be achieved with high-quality data. How can you get good-quality data? Incident Intelligence. In this on-demand session from Pandapalooza, our Group Product Manager, Orr Ganani, joined our Regional VP of Professional Services Sales, Jordan Gamble, to discuss Incident Intelligence and its benefits. Read on to learn more about Incident Intelligence from this webinar.
