If your business is growing, your AWS bill is probably growing with it. Yet, in conference rooms all over the world (or Zoom calls, these days), CFOs are asking “we’re spending how much?!” — while engineering leaders try to explain that the platform is twice as fast and they’ve added some machine learning that is going to absolutely change the game.
In today’s modern age, the most crucial aspect of communication is expression. Various groups express their thoughts or feelings through their work. For example, painters express themselves through their paintings as well as singers express themselves through the way they sing. Writers might make you feel their thoughts while reading some of the articles or books they knew how to write primarily for their readers so the readers will understand their feelings and thoughts.
Today, AWS has announced AWS Network Firewall: a new managed service that makes it easy to deploy essential network protections for Amazon Virtual Private Clouds (VPCs). As a launch partner, Splunk has worked closely with AWS to provide customers an integration to AWS Network Firewall. In today’s blog, co-authored by my esteemed colleague Anush Jayaraman, we’ll first detail the data flow architecture and your options to ingest the AWS Network Firewall data.
The concept of a microservice perfectly fits the structure of a serverless function, which easily enables deployment and runtime isolation for different services. On the storage side, services such as DynamoDB also make it easier to have independent databases for each microservice and scale them independently (when required or desirable). Before we dive into details, please consider whether the benefits of Microservices abundantly outweigh its disadvantages for your particular project and team.
Mattermost Cloud offers our trusted Mattermost self-managed collaboration platform as a software-as-a-service and removes the burden of administration. Organizations are adopting cloud strategies and moving to cloud software. There are costs associated with hosting and securing software, especially in a highly available environment. Deploying and maintaining a self-hosted environment requires expertise and an upfront investment of infrastructure.
Over the past year, we’ve talked to people building and operating the next generation of applications. Across the map, we saw cloud-native applications built upon an ever-increasing number of public cloud infrastructure APIs, tools, and managed services. Modern infrastructure lets anyone create automation, not just a few gatekeepers. This shift is powerful, but comes at the cost of complexity, which we built Relay to manage.
Earlier this year, we introduced the Grafana Cloud Agent, a subset of Prometheus built for hosted metrics that runs lean on memory and uses the same service discovery, relabeling, WAL, and remote_write code found in Prometheus. Thanks to trimming down to the parts only needed for interaction with Cortex, tests of our first release have seen up to a 40% memory-usage reduction compared to an equivalent Prometheus process.
Microsoft Azure is one of the fastest-growing cloud platforms in the world, offering a wide range of products for deployment, testing, and cloud storage. Datadog is committed to maintaining an extensible monitoring solution for Azure’s growing ecosystem that doesn’t require lots of manual configuration. That’s why we are excited to announce the following enhancements to Datadog’s Azure integration.
AWS Network Firewall is a firewall for Amazon Virtual Private Cloud (VPC) with pluggable support for third-party intrusion detection systems like Snort and Suricata. Customers use AWS Network Firewall to guard against unwanted traffic to and from their VPCs.
