AST Prep Flashcards
When it comes to APIs, REST is:
A convention for building HTTP Services/API’s
DynamoDB was built to handle applications at amazon, like amazon.com
True
Kubernetes is:
a. Open source
b. Used to help with the orchestration (automation, deployment, scale and management) of containers
Developers use application code to send HTTP requests to:
API Endpoints
DocumentDB has Point in time restore for up to how many days?
35 days
Which data models does CosmosDB support:
Document, graph, key value, column family
Some advantages of mainframes are:
HA
Massive scalability and performance
PostgreSQL markets itself as an Object-relational database
True
When your customer is going with MongoDB for a number of their microservices, which self-managed licensing model makes the most sense
Ram Pool
Data Caches like Redis are in memory
True
Benefits of Microservices include:
Each microservice can use its own tech stack
You can scale each microservices independently
If one microservice goes down the rest still work properly
Continuous Delivery/Deployment
Starts once the tests of new code are successful
Packages the app to be downloaded by users and or deploy it to a production environment to be used
DynamoDB on its own has out of the box support for the following:
Encryption at rest
Auto scaling
ACID transactions
Database Triggers
Two main benefits of DevOps are:
Better code quality and products
Faster releases TTM
Azure CosmosDB has industry leading security & compliance. They encrypt over the wire and at rest.
True
Event Driven Architectures power modern systems that enable companies to:
Provide a compelling customer experience
Combine everything they know about their customers with state-of-the-art predictive models
Atlas, like DocumentDB can have Analytics nodes that are larger than the operational replica set
False
DocumentDB is assessed to comply with PCI, ISO and is HIPAA eligible
True
How many pre-built, “canned” demos do we have for SA’s to use during PoVs
More than 45
MongoDB Charts is a replacement for a BI tool like Tableau
False
Operational data (like user reviews) that sit in MongoDB are often a source for Data Lakes/Warehouses. This enables broader analysis with other data sets
True
PostgreSQL doesn’t support or conform to all of the features and standards of the SQL:2016 Core conformance standard. This means that:
Moving any application previously built on another RDBMS to PostgreSQL could require some code refactoring
DocumentDB, like Atlas can automatically scale your compute Up and Down
False
Amazon Aurora has out of the box compatibility with which databases
PostgreSQL
MySQL
Data Lakes were designed to store processed, refined data
False
ETL was built to:
Take data from multiple sources combine and transform it and load it into a desired location
For each sales motion, the TFW Planning Framework has:
Common Required Capabilities to consider and the best way to showcase how MongoDB solves it
Links to demos the SA can use to highlight our differentiation
Amazon suggests that rarely can 1 data platform handle every use case, and instead you should use the purpose built database for the job.
True
Amazon claims that documentDB is:
Fully compatible with MongoDB 3.6
Has twice the throughput of MongoDB
Has automatic patching, backups and provisioning
If mainframes are so performant and reliable, why are your customers trying to offload workloads?
Want to get out of the Data Center business and into the Cloud
Its getting hard to find the specialized skill sets needed to run and develop against them
Mainframes are ridiculously expensive. They want to save cost
Continuous integration:
Allows code to be automatically built and tested once added to the main code repository
Allows developers to release features on their own timelines independent of other developers
Amazon documentDB utilizes similar funtionality to replica sets to enable:
HA/DR
Workload isolation/READ ONLY WORKLOADS
RESTful APIs are commonly built to CRUD data on the server:
True
What % of deals need some sort of biz case?
100%
Mainframes are best used for:
zero downtime use cases
Processing huge amounts of smaller transactions simultaneously
For MongoDB sellers, it’s exciting to find out if a company is using a microservice architecture because:
Replacing a Monolith is a large undertaking, but replacing a microservice is easier; a smaller barrier to entry
Managing many services each with their own database is difficult and time consuming
4 main HTTP methods
Get Post Put Delete
Amazon claims that Data Migration Service (DMS) can freely (for the first 6 months) migrate your sharded MongoDB databases, whether on premises or self managed in the cloud, to DocumentDB with virtually no downtime and its as simple as changing a connection string
True
Containers help
Agile DevOps
CICD
Better utilization of resources compared to VMs
This business case has structured interviews with key stakeholders to understand and validate current state business challenges, negative consequences, and a desired future state. It is high touch and includes a formal proposal with a business-focused narrative and a CFO-ready financial analysis of the key financial metrics
BVA
The Sales Process Playbook has tips/tricks & pitfalls to keep in mind during the sales process for each motion
True
Modern companies are moving towards a
Self service BI strategy
Data warehouses and data lakes were built primarily to be a transactional system
False
Kafka / (Message Queues) enable the move to real-time, Event Driven Architectures
True
ETL stands for
extract transform load
API main uses include
Allowing developers to expose their services to many different applications
Allowing different devices and services to connect and interact with each other
Aurora can globally distribute replicas for fast local performance and DR
True
The Sales Process Playbook has Customer Verifiable Outcomes to help know when you are ready to move to the next stage/gate
True
A financial comparison of two (or more) operating models that is used to support deals when MDB has already won the technical decision describes which business case:
TCO
DynamoDB is multi-master which means by default its
eventually consistent
CosmosDB guarantees reads of 1kb or less to return in how many MS
10 MS
Customers can utilize Kubernetes and our Operator/Broker to deploy and manage MongoDB:
Self Managed in the public cloud with Ops/Cloud Manager
Fully Managed in Atlas
On Prem with Ops/Cloud Manager
Kafka / Message Queues give you the flexibility to evolve your IT architectures easily because:
They reduce the need for point to point ETL processes(even if the need to help with the transform at times)
MongoDB connector for BI can help a BI tool like Tableau utilize data in mongodb for
Visualizing data
Spotting market trends
Analyze customer behavior
TFW planning framework has checklists to help with
Prep for TFW
Understanding who should be doing what during TFW
What to follow up with after the TFW
We start this business case in Discovery. Its something we develop over time, not necessarily an exercise done with the customer
3 whys
CosmosDB claims that you will be able to write from any API and read from any API. For Example: write a Document using MongoDB API and read the data in the form of a column-family data model with the Cassandra API.
True
Business Intelligence (BI) is simply the act of visualizing data
False
For MongoDB sellers, it’s exciting to find out if a company is truly practicing CI/CD because:
We know they care about speed to market and productivity
Large focus of the devops practice is:
automation
BVA’s are most applicable to which sales motion
select and replace
If one of the main benefits of devops is faster TTM Mongo can help by
Letting developers focus more time on features instead of schema changes
Letting developers focus on features rather than mapping code needed to translate data into objects
The purpose of a data cache like redis is to
Speed up reads
If one of the main benefits of DevOps is TTM, mongodb Atlas can help by
Automatically scaling their database servers up and down based on demand with 0 lines of code
Can utilize Atlas’ API to take advantage of Infrastructure as Code
Automating and simplifying the management of the database so the team can focus on developing features
Data Lakes and DW were built primarily to be used for analytics
True
Data warehouses by design have strict predetermined data structure (schema) this means that
The data itself is easier to decipher, which allows it to be used in charts, spreadsheets and tables for Business users
it makes the data warehouses difficult and costly to manipulate and support new use cases
Like Atlas, Aurora has auto scale features
True
PostgreSQL supports a wide variety of features such as
Geospatial capabilities
Full text search
JSON/XML support
Containers are more lightweight than VM’s
True
Technical validation comes before business case in the mongodb sales process
False
MongoDB can not be used as in memory cache
False
TCO’s are most applicable for which sales motion
launch and migrate
