CloudWatch Alarms are notifications that are created based on whether a set threshold is met on any one of the CloudWatch metrics. The period for which the metrics are evaluated for an alarm can be set to a custom range. The three states are ok, meaning no trigger, insufficient data, indicating that there is not…
Posts/Projects
Post #185 (AWS) – CloudWatch Agent and CloudWatch Logs Agent
By default your EC2 instances do not upload logs to CloudWatch Logs, they need to have a CloudWatch Logs agent installed with the proper IAM permissions in order to have logs sent to CloudWatch Logs. A benefit to this is you can set up this CloudWatch Logs Agent on your on-prem infrastructure as well to…
Post #184 (AWS) – CloudWatch Logs
Within CloudWatch Logs you have your log group, this is the name of the logs and is usually named after the application the logs are being collected for. You have your log stream, this is the specific instances within an application essentially all the log streams make up the log group. You are able to…
Post #183 (AWS) – CloudWatch Metrics
CloudWatch metrics allows you to gather data from ALL AWS services. A Metric is a specific variable you may monitor, for EC2 it may be CPU util. These metrics belong in namespaces that are isolated from one another to avoid interference with each others data. S3 will be in a different namespace from EC2. The…
Post #182 (AWS) – Personalize and Textract
Personalize is quite simple to understand. It utilizes ML to help in providing personalized recommendations in real-time based on provided input. For instance, let’s say you have an online shop that uses Personalize it will start to pick up certain products that users are buying and provide them personalized recommendations. You can have this data…
Post #181 (AWS) – SageMaker, Forecast, and Kendra
Amazon SageMaker is a serverless service offered by AWS that allows ML experts and data scientists to build ML models. Similar to how transcribe, polly, Rekognition, etc, all use pre-built ML models to analyze a specific type of data except that SageMaker allows you to make your own ML model. First, you accept a range…
Post #180 (AWS) – Comprehend and Comprehend Medical
Comprehend is a service that utilizes NLP, Natural Language processing, it uses ML to find relationships in text. It can find key phrases, places, people, and topics. It can then determine if it is positive or negative, and even group the text files automatically into different categories that it defines based on frequency. Comprehend is…
Post #179 (AWS) – Lex and Connect
Lex is the same technology used to power Amazon Alexa. It utilizes ASR (Automatic Speech Recognition) to convert speech to text, it can recognize intent and is commonly used to power chatbots and automated call center bots. Connect is a cloud based virtual contact center that allows you to accept calls and create contact flows,…
Post #178 (AWS) – Polly and Translate
Polly is essentially the opposite of Transcribe, it is text to speech. You have access to a pronunciation lexicon, this can be used to create pronunciations for certain words or acronyms, such as AWS being pronounced Amazon Web Services. You can also use the SSML, the Speech Synthesis Markup Language this allows you to add…
Post #177 (AWS) – Transcribe
Amazon Transcribe is a speech to text tool that uses Automatic Speech Recognition (ASR) to convert speech from a user into text that can be transcribed as the name details. You can even set Transcribe to automatically remove PII, Personally Identifiable Information, from the gathered text via redaction. This PII could include name, phone number,…