remove EBS from the suggestions

service_capacity_modeling/models/org/netflix/cassandra.py

@@ -211,12 +211,12 @@ def _estimate_cassandra_cluster_zonal(
     desires: CapacityDesires,
     zones_per_region: int = 3,
     copies_per_region: int = 3,
-    require_local_disks: bool = False,
+    require_local_disks: bool = True,
     require_attached_disks: bool = False,
     required_cluster_size: Optional[int] = None,
     max_rps_to_disk: int = 500,
-    max_local_disk_gib: int = 2048,
-    max_regional_size: int = 96,
+    max_local_disk_gib: int = 5120,
+    max_regional_size: int = 192,
     max_write_buffer_percent: float = 0.25,
     max_table_buffer_percent: float = 0.11,
 ) -> Optional[CapacityPlan]:
@@ -462,7 +462,7 @@ class NflxCassandraArguments(BaseModel):
         " this will be deduced from durability and consistency desires",
     )
     require_local_disks: bool = Field(
-        default=False,
+        default=True,
         description="If local (ephemeral) drives are required",
     )
     require_attached_disks: bool = Field(
@@ -478,11 +478,11 @@ class NflxCassandraArguments(BaseModel):
         description="How many disk IOs should be allowed to hit disk per instance",
     )
     max_regional_size: int = Field(
-        default=96,
+        default=192,
         description="What is the maximum size of a cluster in this region",
     )
     max_local_disk_gib: int = Field(
-        default=2048,
+        default=5120,
         description="The maximum amount of data we store per machine",
     )
     max_write_buffer_percent: float = Field(
@@ -513,7 +513,7 @@ def capacity_plan(
             desires, extra_model_arguments.get("copies_per_region", None)
         )
         require_local_disks: bool = extra_model_arguments.get(
-            "require_local_disks", False
+            "require_local_disks", True
         )
         require_attached_disks: bool = extra_model_arguments.get(
             "require_attached_disks", False
@@ -522,8 +522,8 @@ def capacity_plan(
             "required_cluster_size", None
         )
         max_rps_to_disk: int = extra_model_arguments.get("max_rps_to_disk", 500)
-        max_regional_size: int = extra_model_arguments.get("max_regional_size", 96)
-        max_local_disk_gib: int = extra_model_arguments.get("max_local_disk_gib", 2048)
+        max_regional_size: int = extra_model_arguments.get("max_regional_size", 192)
+        max_local_disk_gib: int = extra_model_arguments.get("max_local_disk_gib", 5120)
         max_write_buffer_percent: float = min(
             0.5, extra_model_arguments.get("max_write_buffer_percent", 0.25)
         )

tests/netflix/test_cassandra.py

@@ -92,7 +92,10 @@ def test_ebs_high_reads():
                 estimated_state_size_gib=certain_int(1_000),
             ),
         ),
-        extra_model_arguments={"require_attached_disks": True},
+        extra_model_arguments={
+            "require_attached_disks": True,
+            "require_local_disks": False,
+        },
     )[0]
     result = cap_plan.candidate_clusters.zonal[0]
 
@@ -103,8 +106,8 @@ def test_ebs_high_reads():
     # 1TiB / ~32 nodes
     assert result.attached_drives[0].read_io_per_s is not None
     ios = result.attached_drives[0].read_io_per_s * result.count
-    # Each zone is handling ~33k reads per second, so total disk ios should be < 3x that
-    # 3 from each level
+    # Each zone is handling ~33k reads per second, so total disk ios should be < 3x
+    # that 3 from each level
     assert 100_000 < ios < 400_000
 
 
@@ -123,7 +126,10 @@ def test_ebs_high_writes():
                 estimated_state_size_gib=certain_int(10_000),
             ),
         ),
-        extra_model_arguments={"require_attached_disks": True},
+        extra_model_arguments={
+            "require_attached_disks": True,
+            "require_local_disks": False,
+        },
     )[0]
     result = cap_plan.candidate_clusters.zonal[0]
 
@@ -192,6 +198,41 @@ def test_high_write_throughput():
         extra_model_arguments={"max_regional_size": 96 * 2},
     )[0]
     high_writes_result = cap_plan.candidate_clusters.zonal[0]
+    assert high_writes_result.instance.family not in ("m5", "r5")
+    assert high_writes_result.count > 16
+
+    cluster_cost = cap_plan.candidate_clusters.annual_costs["cassandra.zonal-clusters"]
+    assert 125_000 < cluster_cost < 900_000
+
+    # We should require more than 4 tiering in order to meet this requirement
+    assert high_writes_result.cluster_params["cassandra.compaction.min_threshold"] > 4
+
+
+def test_high_write_throughput_ebs():
+    desires = CapacityDesires(
+        service_tier=1,
+        query_pattern=QueryPattern(
+            estimated_read_per_second=certain_int(1000),
+            estimated_write_per_second=certain_int(1_000_000),
+            # Really large writes
+            estimated_mean_write_size_bytes=certain_int(4096),
+        ),
+        data_shape=DataShape(
+            estimated_state_size_gib=certain_int(100_000),
+        ),
+    )
+
+    cap_plan = planner.plan_certain(
+        model_name="org.netflix.cassandra",
+        region="us-east-1",
+        desires=desires,
+        extra_model_arguments={
+            "max_regional_size": 96 * 2,
+            "require_local_disks": False,
+            "require_attached_disks": True,
+        },
+    )[0]
+    high_writes_result = cap_plan.candidate_clusters.zonal[0]
     assert high_writes_result.instance.family in ("m5", "r5")
     assert high_writes_result.count > 16
 

tests/netflix/test_cassandra_uncertain.py

@@ -150,6 +150,57 @@ def test_worn_dataset():
         },
     )
 
+    lr = cap_plan.least_regret[0]
+    lr_cluster = lr.candidate_clusters.zonal[0]
+    assert 128 <= lr_cluster.count * lr_cluster.instance.cpu <= 512
+    assert (
+        250_000
+        <= lr.candidate_clusters.annual_costs["cassandra.zonal-clusters"]
+        < 1_000_000
+    )
+    assert not lr_cluster.instance.name.startswith(
+        "m5."
+    ) or lr_cluster.instance.name.startswith("r5.")
+    assert len(lr_cluster.attached_drives) == 0
+    assert lr.candidate_clusters.services[0].annual_cost > 5_000
+
+
+def test_worn_dataset_ebs():
+    """Assert that a write once read never (aka tracing) dataset uses
+    CPU and GP2 cloud drives to max ability. Paying for fast ephmeral storage
+    is silly when we're never reading from it.
+    """
+    worn_desire = CapacityDesires(
+        service_tier=1,
+        query_pattern=QueryPattern(
+            # Very Very few reads.
+            estimated_read_per_second=Interval(
+                low=1, mid=10, high=100, confidence=0.98
+            ),
+            # We think we're going to have around 1 million writes per second
+            estimated_write_per_second=Interval(
+                low=100_000, mid=1_000_000, high=2_000_000, confidence=0.98
+            ),
+        ),
+        # We think we're going to have around 200 TiB of data
+        data_shape=DataShape(
+            estimated_state_size_gib=Interval(
+                low=104800, mid=204800, high=404800, confidence=0.98
+            ),
+        ),
+    )
+    cap_plan = planner.plan(
+        model_name="org.netflix.cassandra",
+        region="us-east-1",
+        desires=worn_desire,
+        extra_model_arguments={
+            "max_regional_size": 200,
+            "copies_per_region": 2,
+            "require_local_disks": False,
+            "require_attached_disks": True,
+        },
+    )
+
     lr = cap_plan.least_regret[0]
     lr_cluster = lr.candidate_clusters.zonal[0]
     assert 128 <= lr_cluster.count * lr_cluster.instance.cpu <= 512