Operations | Monitoring | ITSM | DevOps | Cloud

Hi folks! Éamon here. I’m a recent-ish addition to the Solutions Engineering team and just getting my feet wet on the blogging side so bear with me. :) Back in March, we introduced the Grafana Cloud Agent, a remote_write-focused Prometheus agent. The Grafana Cloud Agent is a subset of Prometheus without any querying or local storage, using the same service discovery, relabeling, WAL, and remote_write code found in Prometheus.

While we know the many benefits of going serverless - reduced costs via pay-per-use pricing models, less operational burden/overhead, instant scalability, increased automation - the challenges are often not addressed as comprehensively. The understandable concerns over migrating can stop any architectural decisions and actions being made for fear of getting it wrong and not having the right resources.

Information security (infosec) is a broad field. Its practitioners behave more like artists than engineers. After all, the mandate for security is not “do X”, but instead “ensure no one can do X, Y, Z, ɑ, β, ɣ, etc.”. The array of possibilities leading to infosec failure are vast. It’s like trying to prove a negative, thus making the task near impossible. On one hand we have an impossible task, on the other we have the affordance of time.

Cloud is no longer a differentiator – it’s a strategic requirement for long-term success. So says Forrester’s Benchmark Your Enterprise Cloud Adoption report, and so say our customers, 90 percent of whom choose our cloud products over hosting Server or Data Center versions on-premise (on-prem). Ten years ago, moving to the cloud was about staying ahead of the curve – no longer.

There are two easy ways to make your cloud application faster and they’re homonyms; cash being the first and cache being the second. (Sorry, but not sorry, for the dad joke). The cloud makes it very easy to increase the amount of compute power and therefore performance associated of your cloud resources.

Ten years ago, Amazon found that every 100ms of latency would cost them roughly 1% in sales. This is a pretty clear statement on the importance of user experience! It’s especially true in today’s ultra-competitive market where the cost of switching (to another provider) for consumers is lower than ever. And one of the most common performance issues in serverless architectures is related to elevated latencies from services we depend on.

We’re pleased to introduce you to the latest Elastic Cloud features and functionality. Grab a cup of your favorite beverage and five minutes, and let’s dive in.

Applications have traditionally been run on servers, which have to be closely monitored to ensure there are no hindrances in production. In the case of serverless computing, you no longer have to manage servers, as the onus falls on cloud service providers. Read along to discover more about serverless computing, including some of its advantages and disadvantages. So what actually is serverless computing?

AWS API Gateway is a great service but can be quite expensive, and even cost-prohibitive in some cases. An Application Load Balancer is a viable alternative since it integrates seamlessly with Lambda functions and is also highly scalable and reliable. For very small traffic, API Gateway will probably be the winner, but in high-throughput cases, ALB is capable of providing up to 90% savings.

In this article we are going to consider the two most common methods for Autoscaling in EKS cluster: The Horizontal Pod Autoscaler or HPA is a Kubernetes component that automatically scales your service based on metrics such as CPU utilization or others, as defined through the Kubernetes metric server. The HPA scales the pods in either a deployment or replica set, and is implemented as a Kubernetes API resource and a controller.