AWS Firewall- Samurai Warriors

Samurai are powerful warriors. We also need the same power in our infrastructure to get Control over Security threats over IP or URL Redirect attacks. So let me introduce to you the AWS Managed Firewall.

In MNCs, we have separate Network and Security teams – which is good by the way. They have the proper tool to block incoming or outgoing traffic. For this, they set up a firewall on their side which helps them establish a Network Control Centre. Continue reading “AWS Firewall- Samurai Warriors”

Simplify Generative AI Development: A Look at Amazon Bedrock

While “Generative AI” may have been a term familiar to AI enthusiasts for some time, the widespread adoption of models like ChatGPT has marked a significant turning point.

The overwhelmingly positive response to these AI models, as they break into the mainstream, is a game changer for modern businesses.

As per Bloomberg, the demand for Generative AI will generate software revenue of $280 billion by 2032.

While there are plenty of solutions on the Internet through which businesses can bring Gen AI capabilities to their existing ops, finding the right and reliable one is crucial.

Amazon Bedrock simplifies the creation and scaling of generative AI applications. It comes with pre-trained models and direct integration with different AWS services. This makes it possible to leverage AI effectively.

So, Amazon Bedrock comes out as the perfect ally for businesses looking to add Gen AI capabilities to their operations.

In this blog post let us learn the applications of Gen AI in business ops and Amazon Bedrock helps you leverage Generative AI.

Continue reading “Simplify Generative AI Development: A Look at Amazon Bedrock”

Harnessing the Power of Loki’s JSON Log Parsing in Grafana

To effectively use Loki’s JSON log parsing in Grafana, you need to set up your log collection agent (Promtail or Grafana Alloy). This setup will involve sending structured JSON logs to Loki. Next, you can query and extract the required fields using LogQL in Grafana.

Initially, these logs were simple plain text, often cumbersome and difficult to decode. However, as applications have grown in complexity, a more efficient way to interpret these logs has become necessary.

This is where structured logs come into play. Unlike chaotic plain text logs, structured logs organize information systematically, often using JSON format.

Now, let’s  understand logs better, especially how to decode JSON logs. We’ll utilize a tool called the JSON Loki pipeline stage to simplify the process.

{
"@timestamp": "2024-02-27T14:13:13.714+00:00",
"@version": "1",
"message": "{\"access-time\":\"2024-02-25T14:13:13.697+0000\",\"account-code\":\"viewsynergy.abc.com\",\"remote-address\":\"49.207.192.81\",\"host\":\"gt-cougar-547c68c464-vz2qp\",\"guid\":\"f53a7273-3e58-4d38-bc7a-0d95edbbfbce\",\"thread\":\"http-nio-8080-exec-12\",\"user\":-2,\"is-static-resource\":false,\"url\":\"/v2/payroll-config/income-tax-agent/calculate/7/100\",\"session-id\":\"cce324dfae80d3cfdcb63766b004dba4\"}",
"logger_name": "com.abc",
"thread_name": "pool-1-thread-1",
"level": "INFO",
"level_value": 20000,
"consumer-id": "0"
}

Continue reading “Harnessing the Power of Loki’s JSON Log Parsing in Grafana”

Solving Timeout Issues in Python Django on Kubernetes

The cloud world is constantly evolving, and migrating applications from virtual machines (VMs) to platforms like Kubernetes offers scalability, portability, and ease of management.
However, the migration process is not always straightforward, and sometimes the journey doesn’t go as smoothly as expected. Our Python Django application, which had been running flawlessly on a VM, suddenly turned sluggish and unresponsive after the migration.
Timeouts became a frustratingly common occurrence, and the overall performance of the application deteriorated significantly.
This unexpected slowdown was a major concern, as it impacted the user experience and could potentially lead to lost revenue and customer dissatisfaction.
In this blog post, we take you through the steps we followed to track down the performance issues and identify the root cause of our application’s slowdown in the Kubernetes environment.

Continue reading “Solving Timeout Issues in Python Django on Kubernetes”

How to Build a Developer Metrics Dashboard?

In today’s modern fast world of software technology, success not only depends on writing code lines or launching new features. It depends on understanding how your team functions, finding areas for improvement, choosing the right tool for platform engineering and ultimately optimizing processes to deliver the best results possible. That’s where the use of a developer metric dashboard solution came into play.

A developer’s dashboard serves as a comprehensive central system for displaying the relevant KPIs and metrics for your engineering team. From code quality and deployment frequency to team velocity and bug resolution time, a well-designed developer metrics dashboard offers detailed insights into your teams’ performance, helping to drive continuous growth.

Continue reading “How to Build a Developer Metrics Dashboard?”