Strong data management systems are essential in the digital world because data is essential to enterprises. Due to its scalability, flexibility, and usability, Snowflake, a cloud-based data warehouse system, has grown in popularity. However, just like any other system, mistakes can happen and negatively impact corporate operations.
Having a system in place to identify and alert stakeholders is crucial for reducing the effects of errors. Sending error messages to Slack users or channels is one approach to accomplishing this. Slack is a well-liked network for team communication that promotes easy cooperation, making it a great choice for error notification dissemination.
Setting up a Snowflake task to record the issue and a Slack bot to convey the message to the intended recipients is required for sending error notifications from Snowflake to Slack users or channels. Snowflake’s tasks, which allow users to plan and automate data processing workflows, can be used to automate this operation.
The steps for configuring a Slack bot to send out error notifications are as follows:
In Slack, the first step is to establish a new bot user. Visit the Slack API website and log in using your Slack credentials to complete this. After logging in, select “Create a Slack app” from the menu and then follow the on-screen directions to build a new app. Following the creation of the app, you may add a new bot user by selecting “Bot users” from the “Features” part of the app setup page.
In order to authenticate the bot with the Slack API, we must create an API token for the bot user. To accomplish this, select “Install App” and adhere to the on-screen directions to grant the app access to our Slack workspace. Once the app has been given permission, we can create an API token by selecting “OAuth & Permissions” from the list of options under “Features” on the app settings page. The API token should be copied and saved for further usage. Enable receiving the workspace URL via incoming webhooks as well.
We can next add the bot user to the Slack channels that will receive error messages from Snowflake after creating the API token. Go to the Slack workplace and find the relevant channels there to achieve this. next look for the bot user we created earlier by selecting the “Add apps” option. Once the bot user has been located, click “Add” to add it to the channel.
The last step is to set up Snowflake to use the bot user and API token to send error warnings to Slack. Setting up a Snowflake job that records the problem and instructs the Slack bot to send the notification will do this. Depending on the requirements for error notification, the Snowflake job can be configured to execute at a specific frequency, such as every hour or every day.
We must develop a stored procedure that searches the error log table and extracts the error details in order to configure the Snowflake task. The error message can then be sent from the stored procedure to the Slack bot, which will subsequently relay it to the chosen channels, using the Snowflake API. The bot user will be authenticated with the Slack API using the API token previously generated.
To get error information for queries that were executed within the previous 24 hours, this stored procedure runs a query against the TASK_HISTORY table in the INFORMATION_SCHEMA. A JSON object including the query ID, error code, error message, scheduled time, next schedule time, finished time, and duration for each error is returned as the results. Through the connectors, we can ensure that the results are transferred to our desired place as a table, a sheet, or an Excel file.
This saved process can be modified to meet our unique needs for error notification, such as filtering errors based on particular error codes.
Now, using our method and the Slack token we established, we will integrate this error log with Slack to alert the users. This is done by setting up a snowflake task to run every five minutes (this may be altered depending on the requirement and available credits), which will notify Slack of any issues.
To bring the API endpoint and bot token to configure our tasks in the Slack channel and integrate the notification flow, we should construct two important key components in our script. To ensure a stronger grasp on the logs, we also have a number of security measures and constraints that may be applied from both Snowflake’s and Slack’s ends. The task scheduler built into Snowflake, which manages schedule time management and smooth integration, carries out the timetable.
// set up the Slack API endpoint
var slackUrl = ‘<Our Slack bot API endpoint here>’;
// set up the Slack bot token
var slackToken = ‘<Our Slack bot token here>’;
This task, which is scheduled to run every five minutes, invokes a saved function. The stored method searches the QUERY_HISTORY_ERRORS table of the SNOWFLAKE. Use the ACCOUNT_USAGE schema to look for issues that occurred during the last five minutes. If there are problems, it creates a Slack message payload and uses the bot token and endpoint of the Slack API to deliver it to the selected Slack bot. To keep track of the number of errors that have occurred at a particular time or for a specific length of time, the messages include a counter for each error that is encountered. We may check the status of our task by calling it and using,
Show tasks like ‘task_name’ in task_location
This task and stored procedure can be modified to meet our unique error notification needs, such as by altering the error time window or the Slack message content.
Setting up error notification thresholds and escalation processes is crucial for making sure that urgent problems are dealt with and fixed right away. When establishing these procedures, keep the following recommended practises in mind:
By adhering to these recommendations, you can make sure that your error notification levels and escalation processes are trustworthy, efficient, and capable of handling urgent situations quickly.
Slack is a real-time communication platform that enables teams to cooperate and communicate effectively, therefore, it has several advantages over email in terms of alerting users. As a result, notifications are sent immediately and are readily accessible to all team members who have access to the appropriate Slack channel. Email notifications, on the other hand, run the risk of being overlooked, delayed, or lost in a busy inbox, which could have a greater negative impact on business.
Additionally, Slack offers more personalization options for notifications. Users can set up notifications to be sent in several formats, such as text, graphics, and links, which can be customised to fit certain use cases. Teams can better comprehend the failed job with the help of this flexibility, which can be important for troubleshooting and debugging.
Slack can streamline the entire incident management process because it interfaces with a broad variety of third-party applications and services, like Jira and GitHub. For instance, a Slack bot can automatically generate an incident in Jira, assign it to the proper team member, and link it to the relevant chat message when a failed job is identified. The time and effort needed to manage incidents can be greatly reduced because of this connectivity between Slack and other applications, which leads to quicker resolution times and lower operational expenses.
Slack also offers improved process visibility for incident response. Team members can quickly see who is reacting to an incident, what steps are being taken, and when the situation is addressed when notifications are given using Slack channels. This openness encourages responsibility and can assist teams in determining where their incident management procedures need to be strengthened.
The screenshots below show the inability to distinguish a few clear benefits of Slack over email. The first screenshot displays the failure-related email notification, which simply includes the bare minimum of an ID and a description. The user is additionally shown in the second screenshot being triggered and monitoring the member for a longer period of time.
Although Snowflake is a strong data warehousing technology that enables effective data storage and analysis, it can have faults that have an influence on data processing and analysis, just like any complicated system. Following are some typical Snowflake fault scenarios and solutions that utilise Slack notification:
It’s crucial to set up error reporting processes if we’re to keep our Snowflake data warehouse reliable and accessible. We can make sure that issues are resolved quickly and that severe errors are escalated to the relevant employees by collecting error information and delivering notifications to Slack channels.
We talked about how to automate the process using Snowflake’s stored procedures and tasks, as well as how to build up a Slack bot to collect error notifications from Snowflake. Defining notification thresholds, utilising various notification channels, and routinely testing notification procedures were some of the best practises we discussed for setting up error notification thresholds and escalation procedures.
By adhering to these best practises, we can build a strong error notification system that minimises downtime while assisting you in swiftly identifying and resolving issues. Setting up issue notifications using Slack may give any data analyst, data engineer, developer, or database administrator access to a potent tool for tracking and maintaining the dependability of your Snowflake data warehouse.
Get in Touch to Supercharge your data and analytics journey with our comprehensive services.
By Ankit Kumar Ojha
By Uma Raj
Shreyanth is a dynamic and passionate Data Engineer with a successful track record spanning 4 years. Holding an MTech degree in Data Science and Engineering from BITS Pilani, he has honed his expertise in harnessing data for actionable insights, statistical methods, machine learning, and predictive modeling. With a year of experience as a Product Architect in his repertoire, Shreyanth brings a unique blend of technical prowess and strategic vision to the table. As a vital member of the data engineering team, he plays a key role in developing, designing, implementing, and optimizing data infrastructure, including complex data pipelines, ETL processes, data warehousing solutions, and data management.