10 points by shreevatsa 1 year ago flag hide 27 comments
johnnys 1 year ago next
We implemented a blog-omatic system for our client, and as the traffic grew, the system just couldn't handle it. We had to re-architect the entire thing and shard the database.
codewiz 1 year ago next
@johnnyS I had a similar experience with a marketing-omatic we built in-house. We ended up using a microservices architecture with horizontal scaling to solve the scalability issues.
cpucoder 1 year ago next
@codeWiz interesting, did you use any particular tools or services for the microservices architecture? We're considering the same approach.
codewiz 1 year ago next
@cpucoder I would recommend Kubernetes and Docker for containerization, and Istio for service mesh. And for CI/CD, we used Jenkins X. It's been quite robust for us.
sysadminguy 1 year ago prev next
We've been running a financial-omatic in production for a while now, and we've handled scalability by using load balancers and auto-scaling groups on AWS.
databasejim 1 year ago next
Nice, do you use any specific database solutions for handling the large data sets? We've been struggling with that.
sysadminguy 1 year ago next
@databaseJim we've been using a combination of Amazon RDS and Redshift for our database needs. It's been working well for us.
newprogrammer 1 year ago prev next
I'm working on a-omatic as my first project in production. Any tips for dealing with scalability issues before they come up?
cloudbuddy 1 year ago next
@newProgrammer first, make sure to write efficient code and optimize database queries. And for infrastructure, consider using a cloud provider with auto-scaling capabilities.
juniordev 1 year ago next
@cloudBuddy Thank you! I'm using AWS, so I'll definitely look into their auto-scaling options. Any recommendations for load balancing solutions?
cloudbuddy 1 year ago next
@juniorDev I recommend using the Application Load Balancer (ALB) for HTTP and HTTPS traffic, and the Network Load Balancer (NLB) for TCP traffic. They also integrate well with other AWS services.
seniordev 1 year ago prev next
For high-traffic applications, we've had success with using Kubernetes and a service mesh like Istio. It provides a lot of control and flexibility for handling traffic and scaling.
networkguru 1 year ago next
@seniorDev Have you experienced any challenges with integrating internal and external services using a service mesh?
seniordev 1 year ago next
@networkGuru Yes, it can be tricky to set up at first, but once you get the hang of it, it's quite powerful. It's important to plan out the architecture and have a solid understanding of the different components.
automateenthusiast 1 year ago prev next
I've been working on a new caching layer for our automation system, and it's made a huge difference in handling high traffic and reducing database load.
optimizeguy 1 year ago next
@automateEnthusiast That's great to hear! What caching solution did you end up using? We've been looking into Redis and Memcached.
automateenthusiast 1 year ago next
@optimizeGuy We ended up using Redis with a cluster setup for high availability and scaling. It's been working well for us so far.
testingmaster 1 year ago prev next
When implementing -omatic systems, it's crucial to have solid testing and monitoring in place. Make sure to use tools like Prometheus and Grafana for real-time monitoring.
monitoringfan 1 year ago next
@testingMaster Absolutely! We use a combination of Prometheus, Grafana, and ELK stack for monitoring and logging. It provides great visibility into the system and helps with debugging and performance optimization.
aiguru 1 year ago prev next
For AI-powered -omatic systems, it's important to consider using serverless architectures with function-as-a-service solutions like AWS Lambda or Google Cloud Functions.
serverlessguy 1 year ago next
@aiGuru I agree! We've been using AWS Lambda for our AI-powered -omatic system, and it's been great for handling the variable traffic and scaling automatically.
datasciencedude 1 year ago prev next
For data-intensive -omatic systems, have you considered using columnar databases like Amazon Redshift or Google BigQuery? They're optimized for handling large datasets and perform well with complex queries.
databasepro 1 year ago next
@dataScienceDude Yes, we've used Amazon Redshift for our data-intensive -omatic projects. It's been a game-changer in terms of performance and scalability. The SQL interface is also quite convenient.
realtimestreamingguru 1 year ago prev next
For real-time streaming -omatic systems, consider using Apache Kafka or Amazon Kinesis. They provide robust and scalable solutions for handling large data streams and performing real-time analytics.
streampro 1 year ago next
@realtimeStreamingGuru Yes, we use Apache Kafka for our real-time streaming -omatic system. It's been quite reliable and performant, and the ecosystem around it is quite vibrant.
containermaster 1 year ago prev next
Containerization using Docker is a must for modern -omatic systems. It provides a consistent environment and makes it easy to deploy and scale the applications.
dockerguru 1 year ago next
@containerMaster I couldn't agree more! We use Docker for all our -omatic projects, and it's been a game-changer in terms of portability and scalability.