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Composite AI: The trifecta that is transforming AIOps

CIO

For example, if a company’s e-commerce website is taking too long to process customer transactions, a causal AI model determines the root cause (or causes) of the delay, such as a misconfigured load balancer. First, a brief description of these three types of AI: Causal AI analyzes data to infer the root causes of events.

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Network topologies – A series: Part 1

Xebia

The examples will be presented as Google Cloud Platform (GCP) resources, but can in most cases be inferred to other public cloud vendors. This setup will adopt the usage of cloud load balancing, auto scaling and managed SSL certificates. Network This example will use the same network as from the previous example.

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Azure Virtual Machine Tutorial

The Crazy Programmer

So this was an example in terms of operating systems. So in the second example, The cost will be too lower than building a new PC. Load balancing – you can use this to distribute a load of incoming traffic on your virtual machine. The second option is creating a virtual machine with that much computing power.

Azure 249
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Building Resilient Public Networking on AWS: Part 4

Xebia

One of the key differences between the approach in this post and the previous one is that here, the Application Load Balancers (ALBs) are private, so the only element exposed directly to the Internet is the Global Accelerator and its Edge locations. In the following sections we will review this step-by-step region evacuation example.

AWS 130
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Adding Postgres 16 support to Citus 12.1, plus schema-based sharding improvements

The Citus Data

PostgreSQL 16 has introduced a new feature for load balancing multiple servers with libpq, that lets you specify a connection parameter called load_balance_hosts. You can use query-from-any-node to scale query throughput, by load balancing connections across the nodes. Postgres 16 support in Citus 12.1

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Moving to the Cloud: Exploring the API Gateway to Success

Daniel Bryant

Most successful organizations base their goals on improving some or all of the DORA or Accelerate metrics. DORA metrics are used by DevOps teams to measure their performance and find out whether they are “low performers” to “elite performers.” You want to maximize your deployment frequency while minimizing the other metrics.

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Microservices Architectural Design by using Spring Boot

Perficient

Load Balancer Client If any microservice has more demand, then we allow the creation of multiple instances dynamically. In that situation, to pick up the right instance with less Load Factor from other microservices, we use a Load Balancer Client (LBC) like Ribbon, Feign Client, HTTP LoadBalancer, etc.