Operations teams almost entirely find work to be done in one of two ways:

Avenue has historically solved for the first use case - giving Operations teams their time back so they can spend more time solving vs. searching. Today, with the rollout of Forms, we’re excited to start supporting Ops teams beyond proactively monitoring on their behalf and support them in manually-triggered Playbooks and Workflows.

Avenue Forms introduces a new paradigm to the Avenue Alerting ecosystem. Our customers currently use Avenue to passively monitor their data warehouse. However, we've found that Operations data does not always start and stop with the data warehouse. Often operations data lives outside of your virtual ecosystem. That's why we've created Avenue Forms to give you a way to manage your internal operations on the fly!

Avenue Forms are flexible and can fit a wide variety of use cases. Internally, we use forms to surface feature requests and to help manage our customer support pipeline. Some of our forms-beta users have been adopting Avenue Forms to manage Delivery-Support (driver calls with a failed dropoff reason) or when their in-store staff have an issue to flag.

When can I get started with Avenue Forms?

 Avenue Forms is available now in your workspace. Go to the Forms sidebar item to get started.

You can view and submit your Avenue form by triggering the Avenue Slack bot with a 

 command or a message shortcut then select a webhook monitor with an attached form from the dropdown.

Can I send a link to an Avenue Form to my customers/non Avenue users?

Forms are currently only available to users logged into your Avenue workspace. We do, however, have plans to enable forms to be sent to non authenticated users in the near future.

How does this feature affect my current webhook monitors?

 All your current monitors will be unaffected by this change.

How do manually triggered Signals differ from the Signals we already get?

Signals generated from Avenue Forms work exactly like Signals created from your current monitors. The “row” returned in the Signal is a single instance of a form submission, where the “column” values are user submitted data. Column names in a returned submission are taken from your form elements “dataId” field.

What kind of form inputs does Avenue Forms support?

Avenue Forms currently supports text inputs, text areas, checkboxes, radio groups, dropdown selects, dropdown multi-selects, and markdown based visual components.

Does Avenue Forms support field level validation?

At the moment all fields are optional by default, but can be set as required. Custom field level validation is on the way!

Today, Avenue Launches Forms - allowing Operations Teams to easily create a form that can be used to kickoff a Playbook. Now, Avenue can be used to not only to passively monitor all possible problems, but can be used by Ops teams to kickoff proactive workflows too.

Avenue Launches Playbook Forms

Today, Avenue launches My Tasks, the hub for all of your issues. Track your work, act on your issues and get a summary of your Avenue workspace and how Monitors are contributing to your issues on the My Tasks page.

Previously, Avenue users were sent to the Signals page to manipulate filters and Saved Views to find relevant information like Signals assigned to them, Open for a long time, or with a given tag.

With today's launch, any Avenue user can immediately find issues that need their attention. Without leaving the Dashboard, you can filter issues assigned to you or your team, quick view an issue, and take any appropriate action on it (for example, you can re-assign an issue, resolve it, or even escalate it).

Simply navigate to the Dashboard from the left navigation bar in Avenue to take advantage of this feature — no further action is required!

My Dashboard — a central hub for all of your issues.

All users will have access to a Dashboard catered to them, but some features may be disabled depending on the user’s role permissions. See 

 for more information and email support@useavenue.com for early access!

Issues are sorted in order of when they were created. Latest issues will be at the top of the list.

Simply click on an issue from the Dashboard to quick view an issue. Click on the see details button to be navigated to the issue’s details page.

How do I apply filters to the issues on the Dashboard other than the available filters Escalated, In Progress, and Unassigned?

Escalated, In Progress, and Unassigned are quick filters available in the Dashboard. To apply more filters, click on the plus icon button next to the quick filters.

If you find yourself repeatedly filtering the Dashboard based on certain criteria, you can create your own quick filter by clicking on the list icon button. You will be prompted to title this quick filter. Going forward, simply click on the list icon button and then click on the title of your saved quick filter to easily apply all set filters.

Avenue Launches My Tasks. A single view for all Avenue Signals assigned to you so you can spend less time searching and more time solving.

Avenue Launches My Tasks

Today, we're excited to announce the launch of Playbooks.

Playbooks allow users to create an actionable set of tasks that define the resolution criterion for a signal. Each time a signal is triggered, Avenue will attach the playbook associated with the monitor the signal was triggered from. Opening the signal on Avenue will allow users to see detailed instructions on how to accomplish each Playbook task, and also allow the user to reassign the task to other members in their organization.

To make creating Playbooks even easier, we’ve also introduced the concept of Playbook Templates. This feature allows you to create a Playbook once but use it across multiple monitors. This is especially helpful when you have multiple monitors that produce signals requiring the same set of steps used to drive an issue to completion.

Currently, operations teams have to manage an external set of tasks or runbooks in order to resolve a signal when sent from Avenue. It is also hard to keep track of which team member is responsible for any given step of the resolution process. Keeping track of stream of work is hard and can cause confusion across operations teams.

With Playbooks, Ops teams will be able to stay on top of their signal resolution process and make sure all issues are resolved in a timely manner using the same steps each time. This will help ensure consistency across teams and make sure everyone is working together on resolving issues for customers quickly.

Here’s how it works: when creating a new monitor, you will now be able to create a new Playbook or attach a Playbook Template. The tasks within the Playbook can be either auto assigned or manually assigned to a team member. After a signal is triggered, Tasks will appear on the signal details page so that team members can check them off as they are completed and uncheck them if they need to look at the task again. They can also simply reassign the task to another team member.

To start using Playbooks today, click on the “Playbooks” button on the sidebar. From there, fill out the form outlining steps needed to resolve any signal.

If you want to attach the Playbook to an existing Monitor, navigate to the Monitor form and scroll to the bottom. From there, click on “Playbook Template” and select the Playbook that was just created.

The next time a signal fires, the tasks associated with the Playbook will be shown on the Signal Details page.

Avenue Launches Playbooks

Avenue Slack users rejoice! Today we are excited to release a major version update to our popular Slack integration! Since its launch, the Avenue Slack app has become our most used integration by far, and dispatches tens of thousands of alerts from Avenue to Slack daily. Now, with version 2.0, our users can expect a more delightful and consistent experience when interacting with our Slack App.

The App Home provides a place for Slack users to quickly get guidance on how to use our app, and also lets users initiate a custom emoji sync between Slack and their linked Avenue organization.

When signals are auto-resolved, Avenue will properly let Slack users know so it is no longer ambiguous whether a signal was resolved automatically or by a sneaky cat.

Updates to signal states are now reflected in the Slack message thread, saving users a trip to the Avenue signal page.

The signal status is now represented by emojis on the root signal message. 🔴 means an issue is open, 👀 means an issue was acknowledged, 🟢 means an issue was resolved, and 🔁 means an issue was re-opened.

Slack profile association from with an Avenue user

When commenting on a signal in Avenue, members who also have a Slack account are now able to associate their Slack profile to their Avenue account.

Actors in the signal audit log no longer show up as anonymous actors, like “#blog-demos assigned issue to …” and instead correctly show the source actor from Slack.

Who doesn’t love their Slack custom emojis? Now you can bring them with you to Avenue!

Sometimes, we see a message in Slack and want to trigger an Avenue alert with

, only to end up closing out of the view generated by the slash command just to copy some data from the original message into the view. Now, Slack message shortcuts allow you to bring that context with you!

Another alternative to triggering an Avenue alert with

, Workflow Steps enable Slack power users to build complex workflows with Avenue webhook monitors!

To take advantage of all the new features introduced in version 2.0, simply re-authenticate the Slack app from the organization settings page. For users that want to enable the

Slack profile association with an Avenue user

feature, they will have to step through the Slack authentication flow themselves. Please note that previously, the Slack authentication flow was only enabled for Avenue org admins. Now, all members of an Avenue organization can initiate the Slack authentication handshake, but non-admins will receive a reduced set of permissions.

Why are normal members now allowed to initiate a Slack authentication handshake?

A key change v2.0 introduces is enabling both Avenue org admins and regular members to initiate a Slack authentication handshake. A Slack app is comprised of two sets of permissions.

User permissions enable a Slack app to access a particular Slack user’s personal data in Slack, and also act on behalf of that user. These permissions can only be conferred to Avenue by the Slack user who owns the Slack account Avenue is attempting to access. Bot permissions enable a Slack bot user (aka the Avenue app’s “user” you see posting signal alerts into channel) to perform various actions you would expect a bot user to be able to do. Previously, when an organization admin initiated the Slack permissions handshake, we would only request bot permissions. Now, in addition to storing the bot permissions, we also maintain a set of Slack user permissions per Avenue user to support

Slack profile associations with Avenue users.

When a regular member (non-admin) of my Avenue organization initiates a Slack authentication handshake, what are the exact permissions granted to them?

Today Avenue is excited to release a major version update to our popular Slack integration!

Avenue Launches Advanced Slack Sync

You can now overwrite signal titles and bodies on a per subscriber basis. This will allow users to send different messaging to each subscriber and even message their own customers directly from Avenue. We also launched a brand-new markdown editor to support rich text for all notification destinations that support it!

You can now configure your monitors to be checked at any cadence or time that you desire using cron syntax. Likewise, you can also explicitly configure the timezone that you’d like to use for your monitor schedule! Navigate to the Create Monitor Form to check it out and don’t hesitate to let us know if you have any questions!

We posted about the launch of Import from DBT & Metabase. Avenue is launching a way to make using existing metrics 10x easier.

If you're already using Metabase for metrics collection and analysis, dbt for data transformation and enrichment, or both for a hybrid approach, then there is now a way to get your data from those tools into Avenue quickly and easily.

Avenue August Product Updates

Avenue has launched support for importing data models directly from

. If you're already using Metabase for metrics collection and analysis, dbt for data transformation and enrichment, or both for a hybrid approach, then there is now a way to get your data from those tools into Avenue quickly and easily. These data models will be mapped to

allowing users to create monitors and get alerted on mission critical events right away.

Metabase is an open source software that provides an easy way to collect, store and visualize data. It allows you to build interactive dashboards from a variety of sources, including databases and marketplaces like Salesforce and Stripe. You can use these dashboards as part of your reporting process or share them with others within your organization so that everyone can see what's happening with their most important metrics.

dbt is an open-source framework for running, testing and documenting SQL queries. It allows you to bring a software-engineering-style discipline to your data analysis work. It has many features that make it easier to use SQL queries in a well-documented way. dbt’s simple concept—understanding that SQL queries are software components—gives you a powerful way to bring software-engineering techniques to bear on your data analysis work.

Before the Metabase and dbt integrations, there was a time-consuming manual process that would have to be completed each time a new monitor was created in Avenue. You would have to copy queries from your Metabase instance or dbt manifest files, open up your Avenue workspace and manually paste these queries into the SQL editor when creating a Data View. This would cause a lot of back and forth between the tools and increase the time it took to create monitors on mission critical business events.

The new Metabase and dbt integrations into Avenue are not only a huge time saver for users, they also reduce potential errors by streamlining the process of creating, managing, and publishing Data Views. These integrations let users click on one button to import Metabase queries and dbt models directly into Avenue as Data Views. Importing from these sources will save a lot of valuable time for team members and reduce potential errors. People who might not know that much SQL can get up and running in Avenue quickly if they have access to Metabase or dbt.

To get started, click on the “Import” button on the Data Views tab.

For now, we only support importing queries via manifest files. Please refer to the

for more information on how to retrieve this file.

In order to make sure your data models are in-sync with Metabase or DBT, you are currently unable to edit the Data View after it has been imported.

No! We will never store any of your credentials. The credentials are only used during import and are verified by Metabase.

Avenue Launches Import From DBT & Metabase

! Custom transform functions let users write & run arbitrary Javascript code to filter, transform, and enrich the data they receive from their database or data warehouse.

While we love SQL at Avenue, sometimes it's much easier to add, enrich, or filter out data using Javascript. Now, users have the option to use both! Avenue users can monitor for business events using SQL queries then modify the results using a built-in code editor all from Avenue’s web app.

Previously, if customers wanted to invoke custom logic to conditionally trigger an Avenue alerts, they would need to deploy an API or Lambda Function in their own infrastructure and use a webhook destination. Now they can write & edit code all within Avenue, all without deploying any infrastructure.

With custom transforms, users can do things like:

There are many things that are easy to do in Javascript that are ergonomically unsound in SQL. We love SQL but often it’s easier to do complex calculations or date filters using a traditional programming language (like Javascript).

, a serverless WebAssembly runner. Using Suborbital, we are able to allow users to run code in a trusted environment explicitly allowing only the permissions required.

To get started, reach out to us on Intercom to get access to the new feature. Once added, simply navigate to the Monitor create/edit page and scroll to the custom transform section to get started!

An easy way to write custom Javascript filter & transform functions for Avenue monitors, all without deploying infrastructure.

or through Intercom and we will add you to the Beta.

In Avenue, you will see a custom code editor on each monitor form. Here, you’ll see a single function

where you’ll get the data from each row as an object. Here you can add additional fields, transform fields, etc. All you have to do is return a new object based on the input row.

Once you’ve written your function, you can build from the editor and see streaming build logs below. Once you’ve successfully built your function, click deploy and you’re good to go!

Will the function be invoked for testing monitors?

While we won’t run the function for previewing fields, if you test your monitor with the

button, we will invoke the Suborbital function so you can see the end result.

What permissions do I need in order to use Custom Transform functions?

Once you’ve been added to the Beta program, you will need

permissions to write or edit custom transform functions.

from the function, we will remove the row from the query.

What else can I use custom functions for?

We have a lot of upcoming work to add extensibility points throughout the product. We will be enabling custom actions (both manual and event-triggered) soon!

As soon as Suborbital supports the underlying language, we will add support for it! Please reach out to us if there’s a language that your team would like to use for custom filters & transforms.

Avenue launches Custom Filter & Transform Functions! Custom transform functions let users write & run arbitrary Javascript code to filter, transform, and enrich the data they receive from their database or data warehouse.

Avenue launches Custom Filters & Transform Functions

Avenue now offers Signal Views, making it easy to save filtered views of signals and share them across your team.

Avenue's Signals page is your team's control center to all the Signals that have fired from Avenue. Currently, you can use the Signals page to filter and group by everything from Monitor and Assignee to Time to Resolution, Date, and more. However, as we saw more complex combinations of filters, it became increasingly difficult to keep track of each view or easily switch between them. Now, with today's release, you can save custom views as Signal Views and access them from a dropdown in the Signals section of the sidebar.

Save-able Signal Views as an extension of the Signals Page.

Can I update a Signal View after it’s been created?

Yes! In order to do so, simply click the “Update” button on the right hand side of the Signal View Page.

Will changing the filters/group by on a Signals View Page change the View itself?

No. Like the default signals change, those updates are only stored locally. To reset it to the currently saved Signals View, simply click the Reset button.

You can access them from the side bar within the “Signals” dropdown.

Easily create shareable views of all the signals across your organization

Avenue Launches Signal Views

Avenue is launching support for time-series metrics and metric-based monitors! Currently Avenue monitors operate under the paradigm of “rows”. That is, you can receive an alert when a new row appears in your query results, a row is removed, or some values in the row change. Now, customers will be able to identify a 

 column used to infer the order of data points, specify an 

to aggregate on (e.g. 5 min, 1 hr, 1 day), and a 

to alert on when breached. The result is a more declarative, more powerful, and less SQL-intensive monitor configuration experience for all Avenue users!

Currently it takes some rather complicated and cumbersome SQL to express a metric-based monitor in Avenue. For example, let’s say we want to send an alert when “there are more than 50 refunds in the last hour”. We would write a SQL query like so:

Using this query, we’d set up an hourly alert where the “unique column” is the timestamp. Altogether, arriving at this solution is not very intuitive and requires some strong familiarity with the mechanics of Avenue monitors.

If we wanted to express the same use case using a metric alert, we would write some much simpler SQL:

And that’s it! No nested SQL, no complex row added logic! The result is a much more expressive monitor which clearly communicates its purpose and is easy for any operator to modify!

To start creating metric-based monitors today, go to the

, and to learn more about the different ways to configure metric-based monitors, check out

What data sources can I use for metric-based monitors?

You can use any data source available on Avenue as long as the table(s) you’re querying have a timestamp column and value to aggregate into a metric!

What types of aggregation functions can I use?

You can use the following aggregation functions:

Which timezone should my timestamp column be in?

If you store your date data in a timezone other than UTC, please convert it to UTC in your query.

Can I use monitor filters with metric monitors?

Yes! Once you have defined your underlying metric monitor query, you can apply any number of monitor filters to the query afterwards. These filters will be applied

the aggregation function is used to compute the metric value for an evaluation interval.

Can I include my metric value in my signal body?

Yes! You can include you metric value, threshold, and comparison operator in your signal body similarly to how you would with row values for event monitors.

Can I use the same metric in multiple monitors?

Yes! You can create standalone metrics at

and then reference any standalone metric in a metric monitor. This allows you to aggregate and subsequently alert on the same metric in multiple ways.

Where can I learn more about configuring a metric monitor?

https://docs.avenue.so/monitors/metric-monitors

 for all the details on creating metric monitors. For more info on creating standalone metrics 

Avenue is launching support for time-series metrics and metric-based monitors

Avenue Launches Metric-Based Monitors

Any engineer that has had to debug an issue in production will know that logs are a crucial component of the dev-ops toolkit. They’re almost certainly the first place you look when you’re notified that something in your app is broken, so the quality of your logs is highly correlated to the time it takes to diagnose, and ultimately fix, any issue that you run into. The only thing that can make a 2 AM on-call alert worse is the subsequent realization that you’re not going to be able to root cause the problem because it was not adequately logged. In an effort to help you avoid that situation, let’s go through the core traits of a successful logging solution below.

In most cases, a log should be as close as possible to the source of the error. This allows you to highlight the problem with the highest level of fidelity. As you bubble the error up through your call stack, you become more likely to conflate multiple sources of error into one generic log message. Ultimately it’s the difference between knowing that your API failed, and knowing the specific external dependency that caused said failure.

A log message should, at the very least, always contain the contents of the error that it is logging. In the example below, the log message on the bottom is exponentially more useful than the log message on top because it will provide the reader with substantially more information about the root cause of the failure:

Knowing the answer to these types of questions is fundamental to knowing how to fix the issue.

Today your logs are most likely aggregated into some persistent storage like DataDog, Splunk, or AWS CloudWatch. These log stores are fantastic tools for combing through the mountains of logs that your servers emit, but they’re far more useful if your logs are well-structured. In production you should emit your logs in a format like JSON so that your aggregator can properly index your logs. Likewise, rather than emitting a log as a monolithic string, emit it as an object with a key-value pair for each relevant piece of information.

This will allow you to explicitly search for each field, instead of always doing a fuzzy text-search on the content.

Lastly, a log message should be contextually rich. The definition of context will depend on your application, but it should ultimately serve to semantically identify a given log message from other log messages that may have been emitted at the same time or place in your app. In a nightmare scenario where you’re suddenly flooded with a series of errors, the first thing you’ll see is a chronologically-ordered glut of interleaved logs coming from a number of different places in your app.

It's incredibly important to have the capability to filter down these logs to a 

 of a given request, workflow, or other process in your app so that you can make sense of the noise.

Ultimately, identifying and agreeing on the aspects of a good log message is only useful if those qualities are easy for the engineers to implement. Location, content, and structure can mostly be enforced through documented best practices and code reviews. However, making sure that each log message has adequate context is a non-trivial problem. Let’s use Avenue’s distributed workflow engine as an example.

Avenue’s workflow engine is a multi-tenant application that runs thousands of cron jobs every hour to evaluate the conditions of various Avenue monitors, trigger escalations, and more. For a given job, let’s define our base context as a 

. It’s impractical and tedious to independently resolve these values every time we want to emit a log message. A natural alternative is to pass around a context object with these values throughout our entire call stack. This is the approach 

The results are traceable and consistent logs, but the implementation still feels a little clumsy because you are required to pass a context object throughout your entire call stack. Luckily 

 provides us with a way to achieve the same end product without any boilerplate!

OpenTelemetry is a "collection of tools, APIs, and SDKs [used to] instrument, generate, collect, and export telemetry data (metrics, logs, and traces) to help you analyze your software’s performance and behavior.” It’s a 

, and an altogether fantastic collection of software. We can use OpenTelemetry’s NodeJS Context Manager to register and propagate our context object down our call-stack without explicitly passing the object to every function! The magic behind this module (

, which allows asynchronous resources (such as Promises and functions with callbacks) to inherit contextual information from their “parent” resource without explicitly passing around a map to store this metadata. If you’ve used 

 in other programming languages, this concept should feel familiar!

In practice, the developer experience is as follows:

Thus we can instantiate context once at the top of our call stack, provide it to the OpenTelemetry context manager, and leverage it whenever we need to emit a contextually rich log message. Adding context to upstream functions is seamless, and similarly, updating existing log lines to leverage this context took minimal refactoring. If you’ve made it this far, hopefully this pattern can help you bring a bit more structure and consistency to your logs! If you’re interested in learning more about the various applications of async local storage, async hooks, and persistent execution context, this 2020 talk by Shanee Radzewsky is an awesome resource.

Async Hooks: A Journey To a Realm With Persistent Execution Context | Node.TLV 20 | English

Likewise if you’re passionate about observability, building resilient software, and are looking for something new - Avenue is hiring across engineering, design, growth, and more! Check out our 

How Avenue Makes Effective Logging Effortless with OpenTelemetry

New to Avenue: now you can add tags to any Monitor. You can use tags to categorize Signals based on common traits and themes.

Companies scaling their Operations with Avenue end up with a long Signals page that covers several work-streams. As a result, it can be difficult to keep track of common themes. Now, you can tame the chaos with tags. Simply add a tag in the Monitor or Signal Details page and watch them appear in the list views.

Tags are live today! You can create and add them directly in a monitor or signal details page, and edit them in user settings.

Tags to link common traits in monitors and signals.

You can create a tag either directly from the monitor or signal details page by inputting your desired title and clicking the “+” button or in the tag section of the user settings page.

You can only edit tags in the tag section of the user settings page. Tags cannot be edited or deleted in the monitor or signal details page.

You can only delete tags in the tag section of the user settings page. Tags cannot be edited or deleted in the monitor or signal details page.

Do signals and monitors have different tags?

No, tags are consistent throughout both signals and monitors. When you create a signal, it inherits all of the tags currently on the monitor it was created from.

For one level up, try using entity tagging!

Avenue Launches Monitor Tags

Avenue users can now automatically generate 

Teams managing incident response should be able to focus on solving problems. With Avenue, users can automate the human coordination and documentation of that problem solving, including auto-creating and auto-populating Zendesk tickets. Easily execute your team’s full response playbook by including this in your workflows.

Skip the manual work and focus on handling the emergency - we’ll handle the rest.

To use this custom mapping tool, simply navigate to the Monitors page > Create Monitor, and select “Zendesk” as the Notification Type. From there you can map the Monitor results to Zendesk fields.

Does Avenue intend to roll out support for more third party APIs?

Yes! Stay tuned for a few more and check your Avenue workspace’s settings for a sneak peak.

What kind of content can be placed in the mappings?

Users can inject data from their monitor runs as well as hard coded content.

Avenue Launches Custom Actions in Zendesk

 works with trade and technical schools across the country to provide affordable payment solutions for students. They build, manage, and fund custom tuition solutions for high quality trade and technical schools that prioritize student outcomes. Through their specialized software and human support, they facilitate custom Single Payments, Income Share Agreements (ISAs), Payment Plans and Hybrid structures. Mia Share gives more students the ability to pursue affordable, valuable education while helping partner schools improve enrollment, retention, and outcomes.

Understanding Income Share Agreements (ISAs)

The team at Mia Share is fiercely devoted to making education financing more fair by providing alternatives to student loans. Under an income share agreement (ISA), the student receives their tuition in exchange for a fixed percentage of their income. There are constraints around what the student owes each month. If they don’t earn above a set income threshold each month on an annualized basis, they won’t owe anything; only when they surpass the income floor do they owe a percentage of earnings back per month. On the other end of outcomes, the ISA has a cap for money owed, and if the contract ends before the tuition is paid back in full, the agreement is still terminated without any remaining balance or accumulating interest.

The Operations Team at Mia Share had a long list of alerts they wanted to receive, but it meant submitting requests to Engineering for every change, even if it was only to update the Slack channel where they wanted to re-route the alert. That’s when they implemented Avenue.

“The queries are easy to replicate, and I make quick changes to create a new notification,” explains Molly Roberson, Head of Operations at Mia Share. “On the day-to-day, having Avenue gives me tools to keep an overview and understand the system more. I can’t constantly bombard our engineers with new notifications or small changes. I also get to set up notifications when I’m onboarding new team members to help familiarize them with different processes and aspects of our company.”

Mia Share’s Chief Technology Officer, Derrick Ontiveros, was hesitant at first to implement a tool like Avenue. “I was concerned that it wouldn’t be accessible for non-developers and skeptical that it would save us time, but it really has,” he shares.

Before Avenue, Ontiveros would have to allocate resources to alert creation, increase the complexity of Mia Share’s internal systems, and continually manage the list of alerts for Roberson and her team. Now, they have notifications “up and running more easily with Avenue than anything else.”

With their focus on simple, smart, and scalable technologies, the Mia Share team is ready to grow. Internally, they’re focusing on growing the team and continuous product improvement. Strategically, their aim is to increase their product offerings for partner schools and expand to a wider range of trade and technical schools across the country this next year. Underlying both goals is their core mission: “Our goal is to continue making education more accessible to students and to continue giving them alternative options to student loans.”

Operations teams have been the group that works on the edge of a business. They pick up everything that slips through the cracks, and they tend do so with a patchworked and insufficient toolkit. Instead of focusing on preventing fires, they have to figure out where the fires are coming from while they fight them.

It’s a new day for operations teams. Avenue provides all the alerts, monitoring, analysis, and escalations you need, in one place.

Latest posts

Avenue Launches Playbook Forms

Avenue Launches My Tasks

Avenue Launches Playbooks

Avenue Launches Advanced Slack Sync

Avenue August Product Updates

Avenue Launches Import From DBT & Metabase

Avenue launches Custom Filters & Transform Functions

Avenue Launches Signal Views

Avenue Launches Metric-Based Monitors

How Avenue Makes Effective Logging Effortless with OpenTelemetry

Avenue Launches Monitor Tags

Avenue Launches Custom Actions in Zendesk

Independence for Operations Teams: A Customer Case Study with Mia Share

Fireside Chat with Mia Share's Director of Ops Molly Roberson

Avenue Launches Custom Actions in Customer.io

Fireside Chat with Jupiter's CEO & Co-Founder Chad Munroe

Avenue Adds Monitor Grouping and Bulk Actions

How Jupiter Drives Growth & Product Intuition with Avenue

Avenue Adds Role Based Access

Fireside Chat with Vori's Head of Ops Maika Koehl

How Vori Scaled Operations with Avenue

Fireside Chat with AngelList Venture’s BizOps Lead Nigel Koh

Avenue Operational Analytics Modern Data Stack Award

Avenue Launches Mute Lists

Avenue Launches Escalations with Message

Launch Week 2022 | Alerting Conditions + Filters

Launch Week 2022 | Data Views

Launch Week 2022 | Reporting, Grouping, + Signals

Fireside Chat with Blank Street's Head of Data, Ali Salihoglu

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Avenue Launches Advanced Issue Details: All Context and Action in One Place

Introducing Avenue: The First Operations Observability Platform