Add Pravega as Adopter (#3032)

Signed-off-by: ajeshbaby <[email protected]>

Author: ajeshbaby

ADOPTERS.md

@@ -57,5 +57,6 @@ existing functions.
 |[Keptn](https://keptn.sh)|[Chaos Engineering integration in CD](https://www.youtube.com/watch?v=aa5SzQmv4EQ)|[Our Story](https://medium.com/keptn/part-2-evaluating-application-resiliency-with-keptn-and-litmuschaos-use-case-and-demo-f43b264a2294)|
 |[KubeFlare](https://github.com/raspbernetes)|Resilience of microservices on ARM64 (Raspberry Pi) based clusters|[Our Story](adopters/organizations/raspbernetes.md)|
 |[OpenEBS](https://openebs.io/)|[Openebs-CI](https://openebs.ci/)|[Our Story](adopters/organizations/openebs.md)|
+|[Pravega](https://pravega.io/)|To inject faults while exercising quality tests on our product|[Our Story](adopters/organizations/pravega.md)|
 
 

adopters/organizations/pravega.md

@@ -0,0 +1,14 @@
+### **Pravega**
+
+[Pravega](https://pravega.io/) is an open source storage system implementing **Streams** as a first-class primitive for storing/serving continuous and unbounded data. Pravega organizes data into **Streams**. A **Stream** is a durable, elastic, append-only, unbounded sequence of bytes having good performance and strong consistency.
+Pravega Streams are based on an append-only log data structure. By using append-only logs, Pravega rapidly ingests data into durable storage.
+
+### Why do we use litmus
+
+**Pravega** is a distributed system and is deployed on our custom build of Kubernetes having the desired set of microservices, hence we were seeking a tool which can adapt in our environment with minimal alteration and be able to inject faults while exercising quality tests on our product.
+
+Therefore, we chose Litmus Chaos to meet our use cases. The benefits we see in Litmus Chaos are: it is a CNCF project, it supports kubernetes type deployment environment, it has frequent & steady releases, and it's a well maintained tool.
+
+### How do we use litmus
+
+On deploying Litmus Chaos along with its **Chaos Experiments**, we get standard fault injection scenarios like: **pod-network-loss**, **pod-network-latency** & **pod-cpu-hog**, which we introduce on live deployments of a Pravega cluster. This helps us to simulate real time stressful conditions on the setup and to test for its recovery & fault-tolerance behavior, which in turn helps us to improve the overall quality of our product in stable as well as adverse conditions.