Apache Flink is a general-purpose platform for batch and streaming distributed data processing. This talk describes how Flink’s powerful APIs, iterative operators and other unique features make it a competitive alternative for large-scale graph processing as well. We take a close look at how one can elegantly express graph analysis tasks, using common Flink operators and how different graph processing models, like vertex-centric, can be easily mapped to Flink dataflows. Next, we get a sneak preview into Flink's upcoming Graph API, which further simplifies graph application development in Flink. Finally, we show how to perform end-to-end data analysis, mixing common Flink operators and the Graph API, without having to build complex pipelines and combine different systems. We will go through a step-by-step example, demonstrating how to perform loading, transformation, filtering, graph creation and analysis, with a single Flink program.