Denis was a DevOps Engineer at Moonfrog Labs. He has over 7 years of experience and has worked with a variety of technologies in both service-based and product-based organizations.

Should you build your own log analytics platform or buy one of the many many services out there? Well, we evaluated, compared and decided to build a self-managed ELK stack because none of them fit our requirements.

In this session, we will walk through various design choices we made to have a high-performing log analytics cluster, aggressively optimized for cost and support for infinite data scale without exponentially increasing cost. If you are planning on setting up or re-looking at your log analytics, this could be interesting to you.

Business Requirements/Use Cases -

• Log analysis platform (Application, Web-Server, Database logs)
• Data Ingestion rate: ~300GB/day
• Frequently accessed data: last 8 days
• Infrequently accessed data: 82 days (90–8 days)
• Uptime: 99.90
• Hot Retention period: 90 days
• Cold Retention period: 90 days (with potential to increase)
• Cost-effective solution

Areas of Optimizations -

• Application
• Infrastructure

Cost Optimization -

• Replica counts and their impacts
• How to run ELK on Spot instances correctly.
• EBS costs can be high, how to set up Hot/Cold Data storage
• Auto Scaling
• On-demand ELK Cluster

Infinite Data Retention

• How to setup S3 as a hot backup
• Recover on Demand

Numbers/Tradeoffs

• Cost/GB data ingested
• Trade-offs made
• DR Mechanisms

Conclusion

• Building log analytics is not rocket science. But it can be painfully iterative if you are not aware of the options. Be aware of the trade-offs you are OK making and you can roll out a solution specifically optimized for that.

CTO and co-founder of Moonfrog Labs : Kumar Pushpesh, explains why the company built data infrastructure in parallel to games/products, including -

1. Having a scalable system for data ingestion
2. Data design
3. Querying interface — why stick to SQL?
4. Query interface users
5. Data ingestion
6. High throughput stats service
7. Thin client: Badger
8. High throughput Ingestion backend
9. Hot loading to Redshift
10. Data Warehousing
11. Data design in Redshift and data lake
12. Tuning for scale
13. Taking care of Querying patterns of Product Managers and Data scientists
14. S3 as Data Lake
15. On-Demand Data loading and querying: OnDemand Table(s)
16. Flexibility for complicated analysis: Adhoc redshift cluster(s)
17. Scaling up
18. Typical bottlenecks and solutions we tried

Make your app load faster by 100% in the real world.

We will build a complete real-time multiplayer game in Unity. We will check out the different options unity gives for networking, synchronization, and matchmaking. We will explore Photon in unity for this, which is easy to use to build quick prototypes and also has options to scale to real-world needs seamlessly.

Learn about the skill areas they need to develop to succeed in an Indian Game Development Studio.

Most studios are great at conceptualizing, building, and launching new games. But what happens once you launch? Should you just move on to building the next game? Expecting your game to get tons of users and monetize to its full potential just the way you launched it is like expecting rain to fall just because you took your umbrella. Getting the maximum juice out of F2P games is a journey that begins with the launch, and continues to eternity.

But that’s boring, right? Tweaking, optimizing, finessing, sweating the details. Who wants to do grunt work? We’d much rather be building the next blockbuster game. This workshop hopes to bring the oomph back into LiveOps. Together, we will transform LiveOps into an exciting, challenging, and rewarding problem that your team will WANT to solve.

Walk into this 20 min session and get clarity on the fundamental concepts of Growth, Engagement, and Revenue.

Moonfrog Labs Product Manager Vasavadatta Trivikrama delivers a session on the Game Changers: Hyper-casual and Instant Messenger track at Pocket Gamer Connects London 2019 on January 21st to 22nd.

The talk is about sharing what we learned about our players, our game, and the platform with the audience.

Specifically: —

• Product Market Fit
• Key Drivers for Retention
• Tech & Performance
• Messenger as a Distribution Channel

The Game Changers: Hyper-casual and Instant Messenger track was sponsored by Facebook Gaming.