Task migration happens when distributed data processing systems scale in real-time. To handle the task migration process more gracefully, we propose three task migration methods: (i) worker level migration, (ii) executor level migration, and (iii) executor level migration with reliable messaging. We implement our migration methods on Apache Storm. Our experiments show that, compared with Storm's original migration implementation, our methods significantly reduce the performance degradation and the number of task failures during each migration.