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.

As we discussed in our previous post on cloud cost analysis and optimization, with over 60% of all cloud costs attributable to compute, focusing on compute infrastructure spend should be of the utmost priority. In this post we will focus on the public cloud vendors’ pricing models and how to best leverage them all for maximum cost optimization.

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.

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.

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.

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.

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.

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.

Containers, the biggest innovation in the shipping industry, have standardized dimensions so that they can be loaded and unloaded, stacked, transported efficiently over long distances, and transferred from one mode of transport to another. Taking a cue from this, think of a server as a ship and an application as a crate. A couple of decades ago, only one app could be deployed on one operating system meaning, a single crate on a single ship.