In 2017, we saw the rise and eventual takeover of the container orchestration tool, Kubernetes. Although a lot of great alternatives exist such as Docker Swarm, Mesos and Amazon ECS, Kubernetes became the leader for running containers at scale. Its benefits are that it’s Cloud native (it was designed to run applications at scale on Cloud platforms) and the ability to provide a virtual abstraction layer on top of Cloud providers enabling users to deploy their applications consistently between Cloud providers.
Our October DOXLON featured a solid DevOps Exchange line up, covering some very current topics in the DevOps world. We started with Rob Elkin, CTO @ Busuu talking about Serverless, then Matthew Macdonald-Wallace, a seasoned DevOps consultant ranting about how DevOps has been hijacked by marketing and sales teams, and last but not least, Connon MacRae, VP TechOps at Ticketmaster, talking about their journey to DevOps.
Our August DOXLON featured a solid DevOps Exchange line up, covering some very current topics in the DevOps world. We started with Owain Perry and his monitoring solutions at Just Eat. Following Richard Clark took us through how to build a resilient VPC transit network. We closed with Graeme Forbes on the topic of SSL.
When you are working with Java applications, or any application running inside a Java Virtual Machine, JMX provides an easy and platform-native way to extract details from the runtime without making any code changes. This article provides some examples of how to access monitoring information using JMX.
Docker containers are a game-changer when it comes to delivering software. They make development, testing and deployment faster and more consistent. That you already know.
Running an online service isn't easy. Every day you make complex decisions about how to solve problems and often there is no right or wrong answer—just different ways with different results. On the infrastructure side, you have to weigh up where everything will be hosted: on a cloud service like AWS, or in your own data centres, or a combination of the two, or any number of other options.
Open source monitoring can be quite confusing for those who haven't spent a lot of time reading about the options. At Outlyer, we track the most popular standards and then offer wire-compatible endpoints. This helps new customers migrate onto Outlyer with very little effort, and it means we don't invent yet another proprietary standard and create vendor lock-in.
PLEASE NOTE: in February 2017, we rebranded and changed our name from Dataloop.IO to Outlyer. Our agent is still called “dataloop agent”, and relevant code reflects the old name (Dataloop) as well. Thank you for your patience as we update everything.
We had a request today from one of our customers to look into supporting tags on StatsD metrics in Outlyer. The answer was so surprisingly easy I thought I'd do a blog post about it.
We've been making our Grafana 3.0 plugin better so here's a list of the new things. They work in Outlyer today and most of this work benefits the DalmatinerDB open source database. We're aiming to polish up the Linux packages and docs for that by the end of this month.
The pull based architecture of Prometheus makes it quite hard to build a SaaS offering around it. Not many people will be either willing or able to open ports over the internet for scraping metrics. Equally, businesses based around running entire environments per customer fall more traditionally under managed services.