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Memory Leak Due To Improper Exception Handling

In this post, let’s discuss an interesting memory problem we confronted in the production environment and how we went about solving it. This application would take traffic for a few hours after that it would become unresponsive. It wasn’t clear what was causing the unresponsiveness in the application.

Technology Stack

This application was running on AWS cloud in r5a.2xlarge EC2 instances. It was a Java application running on an Apache Tomcat server using the Spring framework. It was also using other AWS services like S3 and Elastic Beanstalk. This application had a large heap size (i.e. -Xmx): 48GB.

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Elasticsearch vs. CloudSearch: AWS Cloud

Today, more than 100 billion searches are conducted every month on the Google search engine alone. Search engine users conduct searches for several reasons including the foundational conversion of information into action. An action could be a decision to purchase, consume information for decision-making, or seek a better understanding of an issue or topic among others. Search engines make information available at our fingertips right whenever we need it. 

In this era of big data, search solutions are useful not only for popular search engines like Google, Yahoo, and Bing but also for enterprises for monitoring and managing the growing volumes of data in their databases to enhance operational efficiency. The enterprise search industry has grown remarkably and is expected to be worth $8.90 billion by 2024.

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AWS CloudWatch + yCrash = Monitoring + RCA

AWS Cloud Watch + yCrash = Monitoring + RCAWe had an outage in our online application GCeasy on Monday morning (PST) Oct 11, 2021. When customers uploaded their Garbage Collection logs for analysis, the application was returning an HTTP 504 error. HTTP 504 status code indicates that transactions are timing out. In this post, we would like to document our journey to identify the root cause of the problem.

Application Stack

 Here are the primary components of the technology stack of the application:

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AWS vs. Google Cloud: Comparing the Giants

AWS and Google Cloud are two key rivals in the world of cloud computing and storage. While the first one is winning people’s hearts with its amazing flexibility and ample features, Google Cloud has managed to firm its feet in the industry with its superb backup services and cost-effectiveness. These two are performing such wonderfully at their respective fronts that it’s tough to pick one out of these two.

If you’re also at the crossroads of picking one, let’s help you decide. In this blog post of AWS VS Google Cloud 2021, we have covered few key differences between these co-workers cloud computing giants. Before we get into the details, let’s figure out the basics of these two.

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AWS Cloud Development Kit (CDK) for Terraform: Enabling TypeScript and Python Support

It’s not a leap to propose that Terraform is the DevOps cornerstone for Infrastructure as Code (IaC). Terraform’s adoption since its mid-2014 release to the software development landscape has been meteoric. More than 8000 organizations are using Terraform for infrastructure automation.

To successfully use the IAC tool, it’s important to optimize HashiCorp Configuration Language (HCL). HCL has become one of the most popular languages on GitHub. Typically though, it’s preferable to work with a familiar programming language rather than learning a new one. The good news here is that the Terraform community, in collaboration with AWS Cloud Development Kit (CDK), recently announced the support of TypeScript and Python for provisioning infrastructure using Terraform. Developers can leverage these languages to optimize the IaC’s tools for many providers and modules.

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7 Challenges With AWS Costs

This article is the first of my series on AWS cost optimization. In this series, I’ll introduce the challenges with AWS costs. I’ll also offer actionable recommendations on how to solve them and perform efficient AWS cost optimization.

Most businesses spend much more on processing and storage than they need. This is often the case with operating expenses for excess capacity to meet peak demand in their on-site data centers.

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Make the Most of Your Migration To AWS Cloud

Introduction

Businesses run workloads on the Cloud when planning new projects, most likely to do with innovation or doing something new. Typical first workloads that we see are web applications, often because of Amazon Web Services (AWS)'s scalability, which is impossible to have the same scalability on-prem. Usually, big companies' innovation teams are the first to use AWS because it's easier to experiment and much easier to launch new things.

In the last two or three years, Artificial Intelligence machine learning has risen as a popular workload. Very few companies today do AI/ML at scale on their environment. It's so much easier to do it on a platform like AWS because of all the data storage services you have and the pre-configured services at your disposal that are much easier to use and leverage than setting up your own tools and applications.

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Snowflake and Salesforce Integration With AWS AppFlow

Amazon Web Services has recently announced a new service called AWS AppFlow, which is a fully managed serverless integration service to allow secure data transfer between various Software as Service providers such as Salesforce, ServiceNow, Snowflake, AWS Redshift, etc. The functionality supports no-code integration with mapping, validating, and merging fields on the fly.

This article covers integrating Salesforce CRM and one of the most popular cloud data warehouses, Snowflake using AppFlow.

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Hybrid Cloud: Cloud Rolls Out To Data Centers in Different Hues

The term "hybrid cloud" in popular vocabulary represents a topology in which an organization's IT infrastructure is spread over public cloud(s) and on-premise data centers. An on-premise datacenter can include the enterprise's own data center or any colocation facility used by the enterprise. Hybrid has also lately been extended to include edge locations whether in a device or in a telecom provider's location. These variants are sometimes also referred to as "private cloud."

Although in a utopian world, the complete data center can be placed in the cloud, in reality, there are invariably some use cases that require workloads to be running on-premise. This is especially true of large enterprises that have considerable IT assets many of which need to continue to reside in the private cloud for various reasons. 

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Serverless Multi-Tier Architecture on AWS

Multi-Tier Architecture

Multi-tier architecture is also known as n-tier architecture. In such architecture, an application is developed and distributed in more than one layer. The number of layers depends on business requirements, but three-tier architecture is the preferred choice and most commonly used. 

This three-tier architecture includes the Presentation tier, the Logic tier, and the Data tier.