Sharing my thoughts and experiences

Lazy Dev


# Migrating from AWS RDS to Aurora: A Step-by-Step Guide

Migrating your database from AWS RDS to Aurora can offer performance improvements, cost-efficiency, and enhanced features. In this guide, we'll walk through the steps to make this migration as smooth as possible.

## Pre-requisites

- AWS Account
- Existing RDS instance
- AWS CLI installed and configured

## Step 1: Backup Your RDS Instance

Before making any changes, it's crucial to backup your existing RDS instance.

```bash
aws rds create-db-snapshot --db-instance-identifier [Your RDS Instance Name] --db-snapshot-identifier [Snapshot Name]
```

## Step 2: Create an Aurora Replica

Create an Aurora replica of your RDS instance.

```bash
aws rds create-db-cluster --engine aurora --replication-source-identifier [Your RDS Instance ARN]
```

## Step 3: Promote Aurora Replica

Once the replica is in sync, promote it to become a standalone Aurora cluster.


```bash
aws rds promote-read-replica-db-cluster --db-cluster-identifier [Your Aurora Cluster ID]
```


## Step 4: Update Connection Strings

Update your application's database connection strings to point to the new Aurora instance.

## Step 5: Test and Monitor

Thoroughly test the new Aurora instance to ensure it meets your performance and reliability requirements.

## Conclusion

Migrating from AWS RDS to Aurora can offer numerous benefits. By following this guide, you can ensure a smooth transition and make the most out of your new Aurora database.



Migrating from AWS RDS to Aurora: A Step-by-Step Guide


# A Day in the Life of an SRE Engineer 

Site Reliability Engineering (SRE) is a discipline that incorporates aspects of software engineering and applies them to infrastructure and operations problems. , SREs play a crucial role in ensuring that services are reliable and scalable. Here's a glimpse into a typical day.

## Morning: Stand-up Meeting

The day starts with a stand-up meeting where the team discusses the status of ongoing projects and any incidents from the previous day.

## Mid-Morning: Code Reviews

SREs spend time reviewing code to ensure that it meets quality and performance standards.

## Lunch: Knowledge Sharing

Lunchtime is often an opportunity for knowledge sharing sessions where team members present on topics of interest.

## Afternoon: Incident Management

SREs are responsible for incident management. They use tools like PagerDuty to stay alert to any issues that may arise.

## Late Afternoon: Capacity Planning

One of the key responsibilities is capacity planning to ensure that systems can handle growth.

## Evening: Documentation

The day often ends with updating documentation, a critical task that ensures everyone on the team can understand the systems in place.

## Conclusion

Being an SRE  is a challenging but rewarding role that requires a mix of software engineering and systems engineering skills. The focus is always on ensuring reliability, scalability, and performance of services.



A Day in the Life of an SRE Engineer 


# Maintaining Infrastructure and Developing CI/CD Pipelines in Google Cloud

In today's fast-paced development environment, maintaining a robust infrastructure and an efficient CI/CD pipeline is crucial. We leverage Google Cloud Platform (GCP) to achieve this. Here's how.

## Infrastructure Maintenance

### 1. Monitoring

We use Google Cloud Monitoring to keep an eye on our resources.

### 2. Logging

Stackdriver is our go-to service for logging all our applications and services.

### 3. Security

We implement VPCs, firewalls, and IAM roles to ensure a secure environment.

## CI/CD Pipeline Development

### 1. Source Control

We use Cloud Source Repositories to manage our codebase.


Maintaining Infrastructure and Developing CI/CD Pipelines in Google Cloud


# Working as a SysAdmin : An Insider's Perspective

System Administrators (SysAdmins) are the backbone of any IT organization, and at Unify, a subsidiary of Atos, the role is no different. This post aims to provide an insider's perspective on what it's like to work as a SysAdmin at Unify.

## Morning Routine: System Checks

The day usually starts with a routine check of all the systems to ensure they are running smoothly. Any alerts or issues from the previous night are addressed immediately.

## Mid-Morning: Patch Management

One of the key responsibilities is to keep all systems up-to-date with the latest patches. This involves careful planning to minimize downtime.

## Lunch Break: Team Meeting

Lunch breaks often include informal team meetings where we discuss ongoing projects, upcoming changes, and any challenges faced.

## Afternoon: User Support

SysAdmins at Unify are also responsible for user support. This includes resolving tickets, managing user accounts, and troubleshooting issues.

## Late Afternoon: Backup and Recovery

Ensuring that all data is securely backed up is a critical task. We use a combination of on-premises and cloud-based solutions for this.

## Evening: Documentation and Reporting

The day usually ends with updating documentation and generating reports to keep track of system performance, security incidents, and other key metrics.

## Skills Required

- Strong understanding of Linux/Unix systems
- Networking knowledge
- Scripting skills (Bash, Python)
- Familiarity with cloud services

## Conclusion

Working as a SysAdmin at Unify offers a challenging yet rewarding experience. The role requires a diverse skill set, from technical know-how to excellent communication skills, making it a fulfilling career choice for those interested in IT operations.



Working as a SysAdmin : An Insider's Perspective


# Developing a Monitoring System from Scratch: A Comprehensive Guide

Monitoring is crucial for maintaining the health, performance, and security of your applications. In this post, we'll guide you through the process of developing a monitoring system from scratch.

## Pre-requisites

- Basic understanding of programming
- Familiarity with Linux/Unix commands

## Step 1: Define Metrics

Identify the key metrics you want to monitor, such as CPU usage, memory usage, and response time.

## Step 2: Choose a Data Store

Decide where to store the metrics. Options include time-series databases like InfluxDB or relational databases like MySQL.

## Step 3: Data Collection

Develop scripts or use existing tools to collect the metrics.

```bash
#!/bin/bash
# collect_cpu_usage.sh

cpu_usage=$(top -bn1 | grep "Cpu(s)" | sed "s/.*, *\$[0-9.]*\$%* id.*/\\1/" | awk '{print 100 - $1}')
echo "CPU Usage: $cpu_usage%"
```


## Step 4: Data Aggregation

Aggregate the collected data for analysis.

```python
# Python code to aggregate CPU usage
import pandas as pd

data = pd.read_csv('cpu_usage.csv')
average_cpu_usage = data['cpu_usage'].mean()
```

## Step 5: Visualization

Use tools like Grafana to visualize the metrics.

## Step 6: Alerts

Implement alerting mechanisms to notify you when metrics cross certain thresholds.

```python
# Python code for alerting
if average_cpu_usage > 80:
    send_alert("High CPU usage")
```



## Conclusion

Building a monitoring system from scratch can be a rewarding experience that gives you full control over your application's health metrics. By following this guide, you can develop a robust monitoring system tailored to your needs.

