Developer teams shipping software frequently are in a constant state of change. Understanding the state of their code at a given point of time is sometimes clear as mud. The Sentry | Sleuth integration is focused on helping developers automate the annoyances of deploying software, tracking the health of a release, and providing clarity on how to resolve critical code issues.
As a Customer Advocate, I talk to a lot of prospective Honeycomb users who want to understand how observability fits into their existing Site Reliability Engineering (SRE) practice. While I have enough of a familiarity with the discipline to get myself into trouble, I wanted to learn more about what SREs do in their day-to-day work so that I’d be better able to help them determine if Honeycomb is a good fit for their needs.
Looking for a way to proactively troubleshoot complex application performance issues? Look no further than Tanzu Observability by Wavefront, which provides easy data ingestion and preconfigured dashboards and can be set up with Spring Boot and Spring Cloud Data Flow (SCDF) integrations.
There is no doubt about the fact that Docker makes it very easy to deploy multiple applications on a single box. Be it different versions of the same tool, different applications with different version dependencies - Docker has you covered. But then nothing comes free. This flexibility comes with some problems - like high disk usage and large images. With Docker, you have to be careful about writing your Dockerfile efficiently in order to reduce the image size and also improve the build times.
The widespread shift to remote working in response to the COVID-19 pandemic has been a disruptive change for countless businesses; some 13% of organisations say they have faced major disruption. But at Canonical, remote working has long been the status quo for many of our teams. In spite of the challenging circumstances in which we all find ourselves, Canonical has been able to continue to operate and support our customers despite their working practices undergoing significant changes.
Working with the right AWS provider can make or break a company, but many companies discover that after a few years, what was once a great fit just doesn’t work anymore. Over time, your needs change, and the provider you’ve been with for years might not be able to provide what you need. Alternatively, maybe your AWS provider simply isn’t living up to your expectations, or perhaps your company is looking to redesign their cloud infrastructure. When this happens, what are your options?
As we continue from our previous post on FinOps vs. DevOps let’s review the primary challenge facing all cloud consumers – identifying and managing current and potential cloud waste. In other words, understanding how efficient your cloud strategy and implementation actually is.. Controlling your cloud spend through a simple visualization is the first step to tackle the problem. Cloud Analyzer, a Spot by NetApp cost optimization tool, is a great starting point.
When looking at an EBS volume in CloudWisdom, you’ll notice that in addition to the metrics we collect from AWS, we also create a number of computed metrics, one of which is netuitive.aws.ebs.iopsutilization. Simply put, IOPS Utilization compares the current number of IOPS that the disk is performing against the total IOPS capacity, and expresses this as a percentage. Thus, if you are currently running 1050 IOPS against a volume whose capacity is 3000 IOPS, the IOPS Utilization would be 35%.
Kubernetes and Docker each play a vital role in modern, microservices-based application development. Since Kubernetes and Docker work in unison to help develop, deploy, and manage large-scale applications – they are not mutually exclusive technologies and they are certainly not in competition with each other. Nevertheless, Kubernetes and Docker are often misunderstood by the non-developer community. To clear up the confusion around Kubernetes vs. Docker, we’ve written this guide.
