Monitoring Pokémon Go: When Your App Breaks All Records
August 03, 2016

Payal Chakravarty
IBM

Share this

In July 2016, the world of gaming was taken over by a new phenomenon – Pokémon Go. Within a matter of days "augmented reality" became mainstream and the app, which was launched mainly in the US and Australia, overtook Tinder and Twitter in the total number of downloads. Pokémon Go surpassed the wildest expectations of its creators, Niantic Labs, and then some.

With popularity comes scale, and with scale comes an overload of requests to the gaming servers. If you are not prepared enough, requests fail and users are frustrated. Frustrated with Pokémon Go crashes, laymen were talking about server status and memes were being created and circulated on social networks. Overnight, websites spun up just to report if the game was up or down in different countries. Being closely related to the APM space, my head was drawing up various ways in which Pokémon Go was perhaps addressing the issue and what monitoring they had to put in place to retain their popularity. Here is my list of probable solutions Pokémon Go could employ to improve the experience for their users and avid fans:

1. Synthetic monitoring

The first and most important question: Is the application up or down, and can users login from around the world?

A game this popular would need to ensure a five nine availability and high Apdex score. With synthetic end-user monitoring, simulated tests can be run from around the world to check for availability and response time as often every few seconds. The simulations can allow you to login to the app and interact with the app as a gamer would.

For example if a user is catching a Pokémon, he makes a HTTP request to an API “catchPokemon” with a set of parameters. Continuously checking if these HTTP requests return a valid response code within a reasonable amount of time ensures the “catching a pokemon” capability is functioning right. This ensures problems are detected and fixed proactively. Synthetic monitoring also helps determine if an issue was due to network latency.

2. Mobile Real User Monitoring

Pokémon Go is a mobile game that is accessed only from mobile devices. Hence Mobile End User Monitoring with crash analytics is imperative to rapidly scope the problem.

Data points – such as how often did crashes occur; what devices, OS and applications versions were being used when the crash occurred; and which geographies did the user come from – are extremely essential to isolate the problem. For example, insights such as “crashes between 6 and 6:30 PM PST were happening from iOS v9 users on West Coast specifically when users attempted to transfer a Pokemon” gives an instant problem scope to delve deeper into.

Further, by tracing individual requests, one can delve into exactly what line of code or what services/microservices could have impacted a particular crash. This data becomes even more insightful if it can be correlated with Twitter sentiment analysis.

A comparison between response time trends and throughput is also another good data point to evaluate if slow responses were due to extra load or an application bug.

3. Server, Database, Application Server Monitoring

In order to deal with scale, the infrastructure to support the game needs to be monitored to spot bottlenecks easily. This requires automatic discovery and health check of all the components that the game runs on.

Considering auto-scaling and high resiliency failover will probably be turned on to cater to the load, the discovery needs to be truly dynamic to track any new nodes that come up. A dynamically discovered topology could have multiple components such as application servers, web servers, databases, load balancers, content distribution networks etc. Memory leaks, CPU consumption, database I/O and space utilization, queues and deadlocks are metrics whose trends need to be monitored continuously with automatic baselines to help identify deviation from normal. Additionally, tracking and correlating log errors via log analysis from these various resources can help diagnose issues rapidly.

4. Predictive anomaly detection for the future

With sudden popularity, one thing that is bound to go out of control is a flood of alerts. To reduce alert noise and ensure that right issues are being worked on, there is the need to have intelligent monitoring alerts. Alerts should be generated based on analyzing, correlating and de-duplicating a set of events and should present sufficient information to enable faster debugging.

As an advanced setup, Pokémon Go monitoring should enable predictive anomaly detection to predict trends on capacity and consumption of backend resources much before they become issues.

Payal Chakravarty is a Program Director of Product Management for IBM Application Performance Management.

Share this

The Latest

December 15, 2017

CIOs around the globe are more determined than ever to achieve digital transformation within their organizations despite setbacks, according to a survey by Logicalis ...

December 14, 2017

The Spiceworks 2018 IT Career Outlook found that 32 percent of IT professionals plan to search for or take an IT job with a new employer in the next 12 months ...

December 12, 2017

Downtime and security risks were present in each cloud environment tested, according to 2016 Private Cloud Resiliency Benchmarks, a report from Continuity Software ...

December 11, 2017

Companies that empower employees with the applications they want and need, and make them readily accessible — anytime, anywhere, on any device — can benefit from measurable gains at the individual and organizational level, according to a survey, The Impact of the Digital Workforce: A New Equilibrium of the Digitally Transformed Enterprise, conducted by VMware ...

December 08, 2017

Metrics-oriented thinking is key to continuous improvement – and a core tenant of any agile or DevOps philosophy. Metrics are factual and once agreed upon, these facts are used to drive discussions and methods. They also allow for a collaborative effort to execute decisions that contribute towards business outcomes ...

December 06, 2017

The recent outage of the University of Cambridge website hosting Stephen Hawking's doctoral thesis is a prime example of what happens when niche websites become exposed to mainstream levels of traffic ...

December 05, 2017

Even as many organizations continue to adopt multi-cloud technologies as part of their dramatic transformation, the mainframe remains a relevant and growing data center hub for many, according to BMC's 12th annual Mainframe Research Report ...

December 04, 2017

Banks are laying the foundation for the digitization of their businesses and anticipate emerging technologies -- from IoT to biometric authentications and blockchain -- to make a substantial imprint on the industry within five years, according to a recent survey of banking professionals commissioned by VMware ...

December 01, 2017

A recent blog on APMdigest — Protecting Network Performance is as Essential as Securing the Network — mentions that performance issues and outages are possible when security tools (like an IPS, WAF, etc.) are inserted inline. However, one easy way to mitigate this concern is to deploy a bypass switch before the inline tool ...

November 30, 2017

While self-service and self-help IT are in common practice, about half of organizations surveyed are still struggling with full deployment and realizing its value, according to a new report by Ivanti and the Service Desk Institute ...