Operations | Monitoring | ITSM | DevOps | Cloud

At CloudZero, we talk to leadership teams at SaaS and companies every day. When it comes to individual customer profitability, the vast majority of them fall into two camps: they’re either taking their best guess — or they have no idea. Typically only the largest companies - those with the resources to dedicate a 5-10 person engineering team to calculating cost - have this level of insight. And you can be sure they yield that knowledge to their competitive advantage!

The ability to monitor your Elastic Cloud deployment is critical for helping ensure its health, performance, and security. Our Elastic Observability solution provides unified visibility across your entire ecosystem — including your Elastic Cloud deployments. Elastic Observability allows you to bring your logs, metrics, and APM traces together at scale in a single stack so you can monitor and react to events happening anywhere in your environment.

When something goes wrong in your network, you often don’t find out about it until your users are affected. By then, you’re on the receiving end of an angry phone call and you’re left scrambling to identify the issue and understand its root cause. As soon as you hang up (if the affected user even lets you hang up), you’re in a race against the clock.

Raygun’s Launch Notes are your regular round-up of all the improvements we made to Raygun last month — from significant features to performance updates.

Log scaling is something that should be top of mind for organizations seeking to future-proof their logging solutions. Logging requirements will grow through use, particularly if not maintained or utilized effectively. There are barriers to successful log scaling, and in this post we’ll be discussing storage volume problems; increased load on the ELK stack, the amount of ‘noise’ generated by a growing ELK stack, and the pains of managing burgeoning clusters of nodes.

Monitoring Jenkins is a serious challenge. Logging is often overlooked, but it provides a wealth of information about the health of your Jenkins instance. The following are some approaches to generating informative logging to these issues, that can help to monitor and provide suitable explanations of where the problems lie; even identifying what the possible solutions are.

When it comes to dashboarding, Kibana is king. Since its release Kibana has changed the way businesses visualize data. Kibana is a fairly intuitive platform and offers some seriously impressive ways to visualize data. In this kibana dashboard tutorial, we are going to help you unlock the full potential of the platform and help you become a Kibana guru. When it comes to visualizing data Kibana is well suited for monitoring logs, application monitoring, and operational intelligence.

You may have noticed how on sites like Google you get suggestions as you type. With every letter you add, the suggestions are improved, predicting the query that you want to search for. Achieving Elasticsearch autocomplete functionality is facilitated by the search_as_you_type field datatype. This datatype makes what was previously a very challenging effort remarkably easy.

Your website is the face of your business - it should urge the customer to buy your product. Knowing this, you spend weeks on a great web design and user experience. But that’s only the visible part, what about your site’s infrastructure? In order to make your website as optimized as possible, you need metrics about everything such as customer behavior, load speeds, proxy request counts, load balancers and more.

The perception that Netdata is only capable of short-term metrics storage is a myth. It’s a pervasive myth we still see in blog posts and through community engagement, despite it being false for more than a year. However, like all myths, this one on metrics storage began with a kernel of truth. When Netdata first flourished as an open-source project in 2017 and 2018, the default metrics database was RAM-only.