MSAT Flashcards
Historically, organizations that built software had separate teams to handle development and IT Operations. As a side effect, that led to the following condition(s):
[select any that apply]
- There were formal gates that existed between the process of “development” and testing/quality assurance, that meant new features got held up waiting for all development work to get done prior to moving into the next phases of the release cycle.
- Conflicts arose between Developers and Operations because developers were incentivized to build highly resilient code, whereas operations were incentivized to move fast getting new code to Production.
- Conflicts arose between Developers and Operations because Developers were incentivized to get new code to Production, whereas Operations were incentivized to ensure uptime and stability of the application(s).
- There were formal gates that existed between the process of “development” and testing/quality assurance, that meant new features got held up waiting for all development work to get done prior to moving into the next phases of the release cycle.
x Conflicts arose between Developers and Operations because developers were incentivized to build highly resilient code, whereas operations were incentivized to move fast getting new code to Production.
- Conflicts arose between Developers and Operations because Developers were incentivized to get new code to Production, whereas Operations were incentivized to ensure uptime and stability of the application(s).
Nicole loves MongoDB and speaks at many user groups and conferences on our behalf.
One of Nicole’s favorite topics is describing how MongoDB helps her achieve compliance by allowing her to distribute her data based on geography. In fact, she is known around the industry for her expertise with respect to this type of horizontal scalability achievable in MongoDB:
Zoned Sharding Compliance Sharding Range Sharding Hashed Sharding Dynamic Sharding
- Zoned Sharding Compliance Sharding Range Sharding Hashed Sharding Dynamic Sharding
Your customer, Jacqueline, is trying to break into new markets and has used MongoDB Community extensively over the past four years. While she knows about sharding, she needs your help making sure she meets the data governance requirements of the new markets into which she will enter.
You let her know that this capability in MongoDB will help:
- Cross-region replication to assign specific data to specific geographies
- Range-based sharding to distribute the data by some logical sequence, like A-Z or 1-1000
- Zone based sharding to assign specific data to specific geographies
- Zone based sharding to evenly distribute data evenly across storage
- Zone based sharding to distribute the data by some logical sequence, like A-Z or 1-1000
x Cross-region replication to assign specific data to specific geographies
x Range-based sharding to distribute the data by some logical sequence, like A-Z or 1-1000
x Zone based sharding to assign specific data to specific geographies
- Zone based sharding to evenly distribute data evenly across storage
x Zone based sharding to distribute the data by some logical sequence, like A-Z or 1-1000
Eric has just launched a new sandwich-ordering-and-delivery application called “Sandwich-O-Matic”, which he built on Atlas.
It’s seeing great adoption, but when demand jumps suddenly he’s needing to quickly log into the Atlas GUI to make sure the necessary compute resources are available…and it’s not a great use of his time, he explains.
You assure Eric there are other options. In particular, you suggest he take advantage of:
- Hiring a team dedicated to watching telemetry from his application
- Adding a replica
- Auto Scaling
- Using the Performance Advisor so he can manually act faster
x Hiring a team dedicated to watching telemetry from his application
x Adding a replica
- Auto Scaling
x Using the Performance Advisor so he can manually act faster
Your customer, Wendy, is bought into the value of MongoDB and the Document Model. She sees Atlas as an ideal tool to help her teams maximize productivity.
However, there’s a problem: Wendy has a team of business analysts already using Tableau, which only works with relational databases. On top of that, she doesn’t want to re-train them to use something different.
You tell her this isn’t a problem because MongoDB offers this tool: [two words]
bi connector
Your customer, Rebecca, has expressed interest in her Development team being able to build data visualizations natively on MongoDB data, without needing to purchase a third party tool.
As a seller, you’re pumped because you know MongoDB built _______ … and that since it was made Generally Available, customers using it have shown a 13% increase in Atlas consumption.
[one word]
charts
In MongoDB, we say that “information accessed together is stored together”. This is one of the fundamental advantages of the Document Model when compared to something like a relational data model.
If somebody asked you to explain in more detail what that statement means, you would say something like:
- Modern applications are written in object oriented code, which means we can just store MongoDB documents in the “front end” of the application code. This translates to many benefits for developers, such as queries being much faster.
- By storing data together that they know will get accessed together, developers can write queries faster, and the queries perform faster, too. That also makes it much easier to make changes to apps, and the entire experience is more intuitive for developers because it maps how they already write code. Many other benefits come from this, too
- The MongoDB Document Model builds on the work already done with relational databases, by allowing developers to just store all their information in one giant table. This makes it so much easier and faster to write applications, and querying data is easier because it all just goes to one big table.
x Modern applications are written in object oriented code, which means we can just store MongoDB documents in the “front end” of the application code. This translates to many benefits for developers, such as queries being much faster.
- By storing data together that they know will get accessed together, developers can write queries faster, and the queries perform faster, too. That also makes it much easier to make changes to apps, and the entire experience is more intuitive for developers because it maps how they already write code. Many other benefits come from this, too
x The MongoDB Document Model builds on the work already done with relational databases, by allowing developers to just store all their information in one giant table. This makes it so much easier and faster to write applications, and querying data is easier because it all just goes to one big table.
Your customer, Kyle, explains he has a team in Frankfurt devoted to analytics and Business Intelligence. However, most of his customers are located in North America, which is where he stores their data. Thus, he’s had a difficult time giving his EMEA-based team timely access to that customer data…which is impeding their ability to add value to the business.
After asking some clarifying questions to better understand their specific challenges and how they’ve tried to solve for them, you suggest MongoDB Atlas because:
- With Atlas, it’s easy to configure Workload Isolation, which is a node eligible for an election and is dedicated to read-only, analytics type work. You cannot place it physically close to your analytics team to reduce latency.
- With Atlas, it’s a well established best practice to devote secondary node(s) to analytics work cases. This has no impact on their eligibility for an election.
- With Atlas, it’s easy to configure Workload Isolation, which is a node ineligible for an election and is dedicated to read-only, analytics type work. You can place it physically close to your analytics team to reduce latency.
- With Atlas, it’s easy to configure Workload Isolation, which is a node dedicated to read-only, analytics type work. It’s great for analytics and because it always sits physically close to the Primary node.
x With Atlas, it’s easy to configure Workload Isolation, which is a node eligible for an election and is dedicated to read-only, analytics type work. You cannot place it physically close to your analytics team to reduce latency.
x With Atlas, it’s a well established best practice to devote secondary node(s) to analytics work cases. This has no impact on their eligibility for an election.
- With Atlas, it’s easy to configure Workload Isolation, which is a node ineligible for an election and is dedicated to read-only, analytics type work. You can place it physically close to your analytics team to reduce latency.
x With Atlas, it’s easy to configure Workload Isolation, which is a node dedicated to read-only, analytics type work. It’s great for analytics and because it always sits physically close to the Primary node.
Your customer, Thomas, has expressed stringent requirements his organization has for RPO and RTO. He asks you to directly answer him how Atlas can help his company to solve for those challenges.
You respond:
- It’s extremely easy to shard the database for scale with Atlas, which means you can easily solve for RPO and RTO.
- Because Atlas provides a three-node replica set by default, it’s highly available and thus your RPO and RTO requirements are solved.
- Backing up a distributed database can be a challenge, and that’s why we designed Atlas with simplicity in mind: you can select from several options and let the fully managed offering handle backups on your behalf.
x It’s extremely easy to shard the database for scale with Atlas, which means you can easily solve for RPO and RTO.
x Because Atlas provides a three-node replica set by default, it’s highly available and thus your RPO and RTO requirements are solved.
- Backing up a distributed database can be a challenge, and that’s why we designed Atlas with simplicity in mind: you can select from several options and let the fully managed offering handle backups on your behalf.
Timmy is worried about changing the database used by their application, because he’s read that modern databases cannot make the same guarantees that they’ve historically enjoyed with Oracle and PostgreSQL.
As somebody well versed in MongoDB, you correct the record by discussing these guarantees that MongoDB can make to an application(s)
Queries Indexes Replica Sets ACID transactions Pick your own shard key
Queries Indexes Replica Sets - ACID transactions Pick your own shard key
You’ve been in talks with Chelsea about her song-sharing application, Stopify. Chelsea has been excited to see the rapid growth of her application, but has reached a point where she needs to better organize her song library.
While Chelsea has taken advantage of Atlas’s autoscale capabilities to handle the increase in traffic, she wants to be smarter about how she stores the songs themselves.
Having decided that her priority is to sort the songs by title, you suggest:
- Chelsea should take advantage of zoned based sharding to achieve her goals
- Chelsea should take advantage of hash-based sharding to meet her requirement
- Chelsea should take advantage of range-based sharding to handle this specific priority
- Chelsea should take advantage of cross-region replication for his data
- Chelsea should take advantage of workload isolation
- Chelsea should continue to scale up using Atlas autoscale
x Chelsea should take advantage of zoned based sharding to achieve her goals
x Chelsea should take advantage of hash-based sharding to meet her requirement
x Chelsea should take advantage of range-based sharding to handle this specific priority
- Chelsea should take advantage of cross-region replication for his data
x Chelsea should take advantage of workload isolation
x Chelsea should continue to scale up using Atlas autoscale
Lisa runs operations for SooperCarz, a high-performance automobile customization company.
SooperCarz is growing, in large part due to their SooperCustom app that allows customers to take pictures of their own car, upload it to the app, and then see how different customizations would look.
Lisa is concerned that the number of potential customizations is growing so fast that she won’t be able to keep up. When she speaks with the MongoDB Solution Architect (SA), they agree that it makes sense to scale horizontally using MongoDB Sharding.
Lisa’s goal is to distribute the data evenly across multiple shards.
Which type of sharding would Lisa use for this?
Range sharding Vertical sharding Hashed sharding Zoned sharding Custom sharding
Range sharding Vertical sharding - Hashed sharding Zoned sharding Custom sharding
Bobby has a problem. His production environment for his gambling app, Parlay Prince, runs on MongoDB on just a single machine.
As his company grows, he wants to ensure his customers have a great experience, but more importantly, he wants to make sure they can always get to Parlay Prince at any time day or night.
To achieve this level of availability, Bobby should consider:
Sharding to achieve high availability
Replication to achieve high availability
Backups so he will always have a copy of Parlay Prince’s data available
Scale up so the customers will have faster performance
Sharding to achieve high availability
- Replication to achieve high availability
Backups so he will always have a copy of Parlay Prince’s data available
Scale up so the customers will have faster performance
Your customer, Kenny, has an app in production that uses MongoDB Atlas. One night he calls you in a panic because he just received a text message that the primary node in his replica set has crashed. “My job is on the line here”, he says, “how could you let this happen?”.
You put his mind at ease by reminding him that:
- MongoDB Atlas is highly available by default; the primary member will fail over to one of the secondary members and his application will remain up and running
- MongoDB Atlas is highly available by default as long as he’s using sharding for elections, the data will be available when he needs it
- He just needs to call support to have them failover the environment; in the meantime, data will be lost, but only for a maximum of his support SLA
- MongoDB Atlas is highly available by default; the secondary member that crashed will fail over to one of the remaining primary members and his application will remain up and running
- MongoDB Atlas is highly available by default; the primary member will fail over to one of the secondary members and his application will remain up and running
x MongoDB Atlas is highly available by default as long as he’s using sharding for elections, the data will be available when he needs it
x He just needs to call support to have them failover the environment; in the meantime, data will be lost, but only for a maximum of his support SLA
x MongoDB Atlas is highly available by default; the secondary member that crashed will fail over to one of the remaining primary members and his application will remain up and running
Your customer, Kristine, is trying to better understand the value proposition of MongoDB and the Document Model. In particular, she wants to understand the advantages of documents helping her engineers build faster applications, faster.
You help her out by translating those technical advantages into the following business advantages.
[select any that apply]
HINT: keep your messaging concise and focus on addressing Kristine’s immediate concern. Just because an answer option is correct doesn’t make it applicable to answering the question.
- By eliminating time-consuming, non-differentiated work associated with relational databases, her developers can speed the process of bringing new apps and features to market.
- Customers (i.e. users of their applications) will have a better experience using the app(s) when those apps perform faster.
- Being able to shard the database allows customers of MongoDB to address locality concerns, such as GDPR.
- MongoDB runs the same everywhere, which makes it relatively very easy to move between environments (i.e. from on-prem to the cloud).
- By eliminating time-consuming, non-differentiated work associated with relational databases, her developers can speed the process of bringing new apps and features to market.
- Customers (i.e. users of their applications) will have a better experience using the app(s) when those apps perform faster.
x Being able to shard the database allows customers of MongoDB to address locality concerns, such as GDPR.
x MongoDB runs the same everywhere, which makes it relatively very easy to move between environments (i.e. from on-prem to the cloud).
