Google Cloud Load Balancer

Google Cloud Load Balancer (GCLB) is a software-defined network load balancer available to all projects on Google Cloud Platform (GCP). The technology is also used internally by services such as Google Search and Google Mail. It is the first point of entry for the majority of HTTP traffic ingressing to Google’s infrastructure.

GCLB is able to scale quickly and effortlessly. It was demonstrated a few years ago that a newly deployed load balancer could handle over 1 million requests per second without a warmup. Continue reading…


Monitoring our systems, networks and server’s performance and activity is one of the duller aspects of administration, and often something that is overlooked until there is a problem. Fortunately, there are many tools that can be used to monitor our system resources with differing levels of complexity and difficulty to configure. One of the simpler tools for getting the details for all the above can be simply derived from the monitoring tools called “Munin”, which is considered as one of the most flexible network resource monitoring systems available for UNIX and UNIX-like operating systems including Linux, FreeBSD, NetBSD, Solaris. Continue reading…

Machine Learning

Machine learning is a variant of artificial intelligence (AI) that makes the systems for self-learning from the data enrolled without being specially programmed. ML aims at the improvement of computer programs that makes the systems to learn for themselves with the accessed data.

The overall learning process initiates with observations from the data accessed such as searches, instructions to find out a particular data. The primary scenario is to allow computers to learn artificially to perform according to our needs. Machine learning is highly related to computational statistics, which aims at prediction-making through the use of computers. Continue reading…

AWS Load Balancer

A load balancer distributes incoming traffic towards multiple EC2 instances in multiple Availability Zones. By this way, a load balancer increases the fault tolerance of the applications. Elastic Load Balancing is used to detect unhealthy instances and directs the traffic only to healthy instances.

Elastic Load Balancing scales the load balancer as traffic to the application changes over time, and it can scale to the vast majority of workloads automatically.

Elastic Load Balancing supports three types of load balancers.

1)Application Load Balancers

2) Network Load Balancers

3) Classic Load Balancers

We can select a load balancer based on the application needs. Continue reading…