Amazon RDS Monitors (Whats New)

Amazon RDS monitors the replication status of your Read Replicas and updates the Replication State field to Error if replication stops for any reason (e.g., running DML queries on your replica that conflict with the updates made on the master database instance could result in a replication error). You can review the details of the associated error thrown by the MySQL engine by viewing the Replication Error field and take an appropriate action to recover from it. If a replication error is fixed, the Replication State changes to Replicating.

Amazon RDS Event Notifications automatically get notified when you encounter a replication error. Separately, you can also monitor the Replication Lag metric and set up a CloudWatch alarm to receive a notification when the lag crosses a particular threshold tolerable by your application.

Comments

How to construct a File System that lives in Shared Memory.

Shared Memory File System Goals 1. MOUNTED IN SHARED MEMORY The result is a very fast, real time file system. We use Shared Memory so that the file system is public and not private. 2. PERSISTS TO DISK When the file system is unmounted, what happens to it? We need to be able to save the file system so that a system reboot does not destroy it. A great way to achieve this is to save the file system to disk. 3. EXTENSIBLE IN PLACE We want to be able to grow the file system in place. 4. SUPPORTS CONCURRENCY We want multiple users to be able to access the file system at the same time. In fact, we want multiple users to be able to access the same file at the same time. With the goals now in mind we can now talk about the major design issues: FAT File System & Design Issues The FAT File System has been around for quite some time. Basically it provides a pretty good file structure. But I have two problems with it: 1. FAT IS NOT EXTENSIBLE IN PLAC...

Common Sense Identification of the Security Problems

Organizations make key information security mistakes, which leads to inefficient and ineffective control environment. High profile data breaches and cyber-attacks drive the industry to look for more comprehensive protection measures since many organizations feel that their capability to withstand persistent targeted attacks is minimal. But at the same time, these organizations make some key information security mistakes, that jeopardize their efforts towards control robustness. Although many firms invest in security technologies and people, no one has the confidence that the measures taken are good enough to protect their data from compromises. Below are the 10 worst mistakes which are common to find, and important to address in the path of mature information security posture. If you analyze the cyber security scenarios, and organizational capabilities, the prevailing trend is a vendor-driven approach. In many cases, security professionals adopt the attitude of procuring...

Ingesting IoT Sensor Data Into S3 With an RPI3

StreamSets Data Collector Edge is a lightweight agent used to create end-to-end data flow pipelines. We'll use it help stream data collected from a sensor. Due to the increasing amount of data produced from outside source systems, enterprises are facing difficulties in reading, collecting, and ingesting data into a desired, central database system. An edge pipeline runs on an edge device with limited resources, receives data from another pipeline or reads the data from the device, and controls the device based on the data. StreamSets Data Collector (SDC) Edge, an ultra-lightweight agent, is used to create end-to-end data flow pipelines in StreamSets Data Collector and to run the pipelines to read and export data in and out of systems. In this blog, StreamSets Data Collector Edge is used to read data from an air pressure sensor (BMP180) from an IoT device (Raspberry Pi3). Meanwhile, StreamSets Data Collector is used to load the data into Amazon's Simple Storage Service ...

Big Data and Cloud Computing

Search This Blog