My previous blog was, “I’ve never used a Mac, and now I need to manage them.” For the second installment of this series I will highlight some key tools and resources for the new Mac admin.
If you think log files are only necessary for satisfying audit and compliance requirements, or to help software engineers debug issues during development, you’re certainly not alone. Although log files may not sound like the most engaging or valuable assets, for many organizations, they are an untapped reservoir of insights that can offer significant benefits to your business.
Back in May, we announced the Kubernetes integration to help users easily monitor and alert on core Kubernetes cluster metrics using the Grafana Agent, our lightweight observability data collector optimized for sending metric, log, and trace data to Grafana Cloud. The integration allows Grafana Cloud users to monitor and alert on Kubernetes cluster metrics. Since the original release, we’ve added new features and enhancements to help our users go even further.
In the latest episode of the Network AF podcast, your host Avi Freedman welcomes his friend and networking pro Cat Gurinski to the show. As a senior network engineer with loads of experience, Cat is most passionate about automation and troubleshooting, and especially loves to use Python and Arista’s pyeapi frameworks in her pursuits. She’s also the current chair of the NANOG Program Committee, and previously worked for companies like Best Buy, Switch and Data, and Equinix.
I have a good sense of how to use traces to understand my system’s behavior within request/response cycles. What about multi-request processes? What about async tasks spawned within a request? Is there a higher-level or more holistic approach?
This blog post defines SRE by explaining SLOs and error budgets, highlighting the innovation vs. reliability tradeoff.
One more “ops” phoneme like DevOps is ChatOps; or conversation-based development/operations. ChatOps has been growing in popularity as communication platforms such as Slack is ingrained in our day-to-day engineering lives. A team lead once told me “if it didn’t happen in Slack, it didn’t happen” showing the emphasis of communication platforms as a system of record.
With Kubernetes emerging as a strong choice for container orchestration for many organizations, monitoring in Kubernetes environments is essential to application performance. Kubernetes allows developers to develop applications using distributed microservices introducing new challenges not present with traditional monolithic environments. Understanding your microservices environment requires understanding how requests traverse between different layers of the stack and across multiple services.
If you are trying to compare all of the best solutions for application performance monitoring and management you may have found that it can be highly complicated to compare all of the available observability tools whilst also trying to keep within a reasonable budget.
